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Trends in Highly Cited Empirical Research in STEM Education: a Literature Review

• Published: 07 December 2022
• Volume 5 , pages 303–321, ( 2022 )

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• Yeping Li 1 ,
• Ke Wang 2 ,
• Yu Xiao 1 &
• Suzanne M. Wilson 3  

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The development of STEM education scholarship takes time and collective effort. Identifying and examining trends in highly cited empirical STEM education research over time will help inform the field and future research. In this study, we searched the Web of Science core database to identify the top 100 most-cited empirical research journal publications in each of three consecutive years. Our analyses revealed consistencies and important changes over the years in terms of the inclusion of articles themselves, the journals where they were published, disciplinary content coverage, and research topics. The results demonstrate that STEM education research is increasingly recognized as important in education, both through publications and citations, and that the field is moving toward conducting more multi- and interdisciplinary STEM education research.

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Introduction

The importance of STEM (science, technology, engineering, and mathematics) education has been well-recognized, not only due to the importance of each component discipline but also the connection and integration of different STEM disciplines. Different from the traditional approach of focusing on individual disciplines such as mathematics and physics, STEM education opens the door for new opportunities and approaches for students’ learning and preparation (see Li, 2018 ). However, new opportunities come with new challenges, as STEM itself is not a discipline. The nature and content of this new integrative field of STEM education scholarship cannot be pre-defined, but emerges from the collective contributions of numerous scholars over time. To gain insights into STEM education scholarship development, we sought to identify and examine trends in empirical research publications that have had high impact in the field over the past 3 years.

A recent research review (Li et al., 2022 ) served as the foundation for this study. In that review, we specified high impact empirical research publications as those that gained high citations. Although many databases are available to search for publication citation counts, the Web of Science (WoS) is the world’s leading scientific citation search and analytical information platform (Li et al., 2018 ). Its core database has been commonly used as a reliable indexing database with close attention to high standard research publications with a peer-review process, thus used in many research review studies (e.g., Li et al., 2018 ; Marín-Marín et al., 2021 ). The WoS core database is more selective than many others, such as Scopus. For these reasons, we searched the WoS core database to identify the top 100 most-cited empirical studies in STEM education published in journals from 2000 to 2021. The search was conducted on September 12, 2022, and allowed us to identify and select those research publications that gained high citations for inclusion up to that day. However, as publication citations keep changing on a daily basis and also over time, it remains unclear whether and how the top 100 most-cited research publications may be changing over time. Learning about publication citation changes provides a glimpse into the dynamic evolution in STEM education research field.

Li et al. ( 2022 ) examined multiple aspects of the top 100 most-cited empirical studies published in journals from 2000 to 2021, including journals in which these high impact empirical studies were published, publication years, disciplinary content coverage, and research topics. We planned for the current study to also focus on those aspects. Different from the recent review, however, the current study aimed to identify and examine possible trends from changes in the top 100 most-cited empirical research publications identified in three different years (i.e., August 2020, September 2021, and September 2022). Taken together, this study was designed to use data from three searches conducted over the years to systematically analyze and report:

consistencies and changes in the top 100 most-cited empirical research journal publications over three years

distributions and patterns of the top 100 most-cited empirical research publications in different journals

disciplinary content coverage of the top 100 most-cited empirical research journal publications and possible trends

research topics being focused on by the top 100 most-cited empirical research journal publications and topic trends

Methodological Considerations

Searching and identifying.

To be consistent with Li et al. ( 2022 ), we used the same process to search and identify the top 100 most-cited empirical research publications in different years. The process started with searching the WoS core database under the field of “topic” (covering title, abstract, author keywords, and keywords plus), using the same search terms: “STEM” OR “STEAM” OR “science, technology, engineering, and mathematics.” Because there are many different categories in the WoS database, we conducted publication searches under the same WoS category: Education Educational Research, on August 9, 2020, September 20, 2021, and September 12, 2022, respectively. In each of these 3 years, the time period of publications was set as starting from 2000 to the year right before the search was conducted. For example, in 2022, all publications from 2000 to 2021 were specified in the search.

After obtaining a list of publications from the search, all publications were placed in descending order in terms of citation counts. Each publication was then carefully checked using the same criteria for inclusion or exclusion (see Table 1 ). The process identified the top 100 most-cited empirical research journal publications. The follow-up publication coding and analysis were then carried out in the same way as Li et al. ( 2022 ).

Accounting for Different Search Category Coverage

During the article search process in September 2022, we noticed that the WoS database has four categories listed under “education”: Education Educational Research, Education Scientific Disciplines, Psychology Educational, and Education Special. It occurred to us that empirical research articles in STEM education may also be published in journals that are not classified and listed under the category of “Education Educational Research.”

Thus, we conducted another search of the WoS database in 2022 under all of the four categories using the same search terms for journal publications from 2000 to 2021. The search returned 9275 publications under “Education Educational Research,” 2161 under “Education Scientific Disciplines,” 247 under “Psychology Educational,” and 15 under “Education Special.” The combined list of all publications was then placed in descending order in terms of citation counts, and each publication was screened using the same inclusion or exclusion criteria (Table 1 ).

As these two searches with the inclusion of different WoS categories were conducted in the same year, possible connections and differences in the inclusion of publications and journals across these two searches will not reveal possible trends over time. However, comparing the results may illuminate the diversity of journal outlets that researchers are using.

Trends in Highly Cited STEM Education Research Publications

Consistencies and changes from 2020 to 2022.

Across the 3 years, 76 publications were identified as included each year. Eleven publications were changed in the 2nd search in 2021 in comparison to the list from the 1st search in 2020; twenty-three publications were changed in 2022. Across the lists between searches in 2021 and 2022, there were 84 same publications and 16 different publications. The results suggest that the majority (76) of high impact empirical research journal publications were stable, over the 3-year period, in terms of gaining high citations. At the same time, quite a substantial number of publications (24) were dropped.

Figure  1 shows the distributions of top 100 most-cited publications in 2022, 2021, and 2020, respectively. Several overall consistencies are noteworthy. Specifically, across these three distributions, the majority of publications were published between 2010 and 2015, suggesting that publications would typically need about 5–10 years to gain extensive exposure to obtain enough citations for inclusion. At the same time, the distribution of those most-cited publications identified in 2022 shows that some more recent publications (2016–2019) also emerged with high citations. Multiple factors might account for this, including possible changes in journal inclusion in the WoS core database or the appearance of high quality research that was disseminated in high profile ways. Further examination of possible contributing factors is beyond the scope of this study.

Distributions of the top 100 most-cited empirical research journal publications in STEM education over the years in three different searches

Table 2 provides the top 10 list of most-cited publications identified from each search. Nine articles (with citation counts bolded) appear each year. In particular, the top 4 are the same across the 3 years. All top 10 articles from the 2021 search made it to the top 10 list again in 2022 search. There is one article difference of inclusion in the top 10 list between 2021 and 2020 searches, and two article differences of inclusion in the top 10 between 2022 and 2020 searches.

Table 2 also shows that all of these most-cited articles were published between 2008 and 2013. The top 10 most-cited publications in 2020 had an average of 180 citations (range, 134–271 per article). In 2021, the articles had an average of 226 citations (range, 180–352). For the top 11 (with two articles in a tie at the 10th place) in 2022, the average was 263 citations (range, 211–421). The nine articles that appeared each year had an average of 185 citations with a range of 140 to 271 in 2020, an average of 231 citations with a range of 192 to 352 in 2021, and an average of 272 citations with a range of 211 to 421 in 2022. The results again provide a clear indication of increased citations for publications over time, albeit with different increasing rates for different publications.

We also observed that the top 10 list of most-cited empirical research publications were published in different journals, but not in a journal specifically on STEM education. In fact, there was no well-established journal in STEM education before 2019 (Li, 2019 ). It is not surprising that the top 10 list of most-cited empirical research articles in STEM education were published in other well-established journals in education or science education at that time. The results suggest the potential value of examining what journals published highly cited empirical research in STEM education and related patterns.

Distributions and Patterns of Highly Cited Publications in Different Journals

We identified and sorted all journals in which publications appeared. Forty-eight journals published these articles across the 3 years (see Table 3 ), 43 journals published the top 100 identified in 2022, 41 journals in 2021, and 40 journals in 2020. Thirty-five of these journals appeared in all three searches.

Thirty-seven journals were covered by SSCI (Social Sciences Citation Index) and 11 were covered by ESCI (Emerging Sources Citation Index). These are clearly well-established and quality journals in the professional community. Moreover, the majority of these journals have a long publishing history, with 35 journals being established 30 or more years ago, and 13 journals having less than a 30-year history. Eleven journals have been established since 2000, eight SSCI journals and three ESCI journals. This suggests that the most highly cited empirical research has been published in well-established and reputable journals with a long publishing history. It is not surprising as STEM education itself has too a short history to establish top journals (Li et al., 2020 ).

To take a closer look at the possible impact of different journals, we examined the top 10 journals and their publications from the list in Table 3 . These 10 journals contributed 57 articles (57%) for the top 100 collection from 2022 search, 56 articles (56%) for the top 100 collection in 2021, and 53 articles (53%) for the top 100 collection in 2020. The results provide clear indications that these 10 journals carried a heavy weight in publishing high impact research articles from the three searches. All of these 10 journals were SSCI journals. They all had 30 or more years of history, except one journal, International Journal of STEM Education (IJSTEM), that started to publish in 2014 (Li, 2014 ). In fact, IJSTEM is the only journal, out of the 48 journals in the list, with a clear focus on STEM education research. The result provides a confirmation about the initial stage of STEM education research journal development at this time (Li, 2018 ; Li et al., 2020 ), and the leading journal status of IJSTEM in promoting and publishing STEM education research (Li, 2021 ).

Among the 48 journals listed in Table 3 , we classified them into two general categories: general education research journals (without a discipline of STEM specified in a journal’s title) and those with STEM discipline specified in a journal’s title, an approach similar to what we used in a previous research review (Li et al., 2020 ). Thirty journals spoke to general educational education research readers; 18 to readers in specific discipline(s) of STEM. The result suggests that researchers published their high impact empirical research in STEM education in a wide range of journals, with more in general educational research journals as these journals tend to be well-established with a long history, and spoke both to scholars with interests in STEM and to broader communities.

Figure  2 shows that the distributions of the top 100 articles over these two types of journals were very stable across these three searches, with about 50% of the articles published in educational research journals and 50% in journals with STEM discipline(s) specified.

Distributions of top 100 most-cited empirical research publications in general and STEM-specific journals. Note: 0 = journals without STEM discipline specified, 1 = journals with STEM discipline specified

Going beyond the cumulative counts of these publications in two types of journals from each search, Fig.  3 shows the distributions of top 100 publications in each type of journal over the years for each search, where dotted line segments refer to the distributions in journals without STEM discipline specified and solid line segments refer to the distributions in journals with STEM discipline specified.

Trends of top 100 most-cited empirical STEM education research publications in general vs. STEM-specific journals, 2020–2022

Overall, there are some general consistencies in trends between the group of dotted line segments and the group of solid line segments, an observation consistent with what we learned from Fig.  2 about overall distributions of publications. However, we also noticed that the dotted line segments stay above the solid line segments from 2009 to 2012, and solid line segments tend to stay higher since 2014 especially from the 2022 search. The results suggest a general trend that those highly cited articles tended to be published in general educational research journals before 2013, but started to have more in journals with content discipline of STEM specified after 2013 in recent search. There are many possible reasons for this trend (e.g., Li et al., 2020 ; Li & Xiao, 2022 ; Moore et al., 2017 ; Wilsdon et al., 2015 ). Researchers might have developed disciplinary consciousness in publications, especially when STEM education publications started to pick up since that time. There is also evidence that there has been a rise in higher education in the pressure to publish, both due to the use of productivity metrics in universities and funders’ use of publication records in evaluating research grants. It may be that, on the global front, institutions of higher education are broadening the list of recommended outlets for publications to STEM-specific journals. This result may also relate to disciplinary content coverage specified in these top 100 publications in different searches, a topic that we will examine further in next section.

Disciplinary Content Coverage

The top 100 most-cited empirical research publications in STEM education were identified through topic search of specific terms (“STEM,” “STEAM,” or “science, technology, engineering, and mathematics”), as it was done in other research reviews (Li et al., 2020 , 2022 ). However, the author’s self-inclusion of such identifier(s) did not mean that all four STEM disciplines were focused on in their studies. Thus, we took a further look at each publication to examine if it focused on a single discipline of STEM or multiple disciplines of STEM.

Figure  4 presents summarized results. The vast majority (75% or more) of these top 100 highly cited articles focused on multidisciplinary STEM education. There is a small but notable change in disciplinary foci between those publications identified from 2022 search and those publications from 2021 and 2020 searches: 25 publications on a single discipline of STEM and 75 on multidisciplinary STEM education from 2022 search, while about 15 publications on a single discipline of STEM and 85 on multidisciplinary STEM education from 2021 and 2020 searches. It would be interesting to see how the disciplinary foci emerged from those highly cited empirical research publications evolve.

Disciplinary content coverage in top 100 most-cited articles, 2020–2022. Note: 1 = single discipline of STEM education, 2 = multidisciplinary STEM education

To take a further look at possible changes across different searches, Fig.  5 presents the distributions of top 100 publications with different disciplinary content coverages from 2020 to 2022. We used solid line segments for the distributions of publications on a single discipline of STEM and dotted line segments for the distributions of publications on multidisciplinary STEM education.

Trends in disciplinary content coverage, 2020–2022

Several general consistencies in trends between the group of dotted line segments and the group of solid line segments, an observation consistent with what we learned from Fig.  4 . At the same time, we also noticed that no publications on a single discipline of STEM before 2011 made to the list in 2021 and 2022 searches, and more publications on multidisciplinary STEM education after 2015 made to the list in these two recent searches than the 2020 search. The results suggest a possible trend of shifting research interest and development toward multi- and interdisciplinary STEM education in the field through recent publications and citations.

Research Topics

To examine research topics, we used the same list of topics from previous reviews (Li & Xiao, 2022 ; Li et al., 2019 ). The following list contains seven topic categories (TC) that was used to classify and examine all publications identified and selected from the three searches in this study.

TC1: Teaching, teacher, and teacher education in STEM (including both pre-service and in-service teacher education) in K-12 education

TC2: Teacher and teaching in STEM (including faculty development, etc.) at post-secondary level

TC3: STEM learner, learning, and learning environment in K-12 education

TC4: STEM learner, learning, and learning environments (excluding pre-service teacher education) at post-secondary level

TC5: Policy, curriculum, evaluation, and assessment in STEM (including literature review about a field in general)

TC6: Culture, social, and gender issues in STEM education

TC7: History, epistemology, and perspectives about STEM and STEM education

Consistent with the coding practice used in the previous reviews, we assigned each publication to only one topic. When there were cases that more than one topic could have been used, a decision was made after discussion.

Figure  6 shows that more publications on four TCs (i.e., TC3, TC4, TC5, and TC6) were more highly cited than articles focused on the other three TCs (i.e., TC1, TC2, and TC7). Moreover, TC4 (STEM learner, learning, and learning environments at post-secondary level) and TC6 (culture, social, and gender issues in STEM education) were the two TCs in 2021 and 2020 searches that had the most publications. In 2022, culture, social, and gender issues in STEM education was the focus of many more publications than the other TCs. The results suggest that publications in TC4 and TC6 were more likely to gain high citations than publications in other TCs, and the trend seems to go further for publications in TC6 but not for TC4 in 2022 search. At the same time, it is a bit surprising to observe that teaching, teacher, and teacher education in STEM in K-12 education (TC1) and teachers and teaching in STEM at post-secondary level (TC2) were not popular topic areas among those highly cited research publications. It would be interesting to see if possible changes may take place in the future.

Trends in research topic distributions, 2020–2022

In comparison to what we can learn from previous research reviews (Li et al., 2020 ; Li & Xiao, 2022 ), the results from this study seemingly present a different picture in terms of the “hot” topics. However, it should be pointed out that this study was restricted in identifying and selecting high impact empirical research publications in STEM education from the WoS database, different from previous reviews in terms of both journal coverages and the scope of publication inclusion. In fact, there were many highly cited research reviews and conceptual papers in STEM education but excluded from review in this study.

Consistencies and Changes in the Top 100 Most-cited Empirical STEM Research Journal Publications Identified from Two Searches Using Different WoS Categories

Now we come to the two searches conducted in 2022 using different WoS categories, as mentioned above. One search was conducted using one category (“Education Educational Research”). The results of the top 100 most-cited publications were presented above together with the results from 2021 and 2020 searches. The second search was conducted using all four categories listed under “education,” including “Education Educational Research,” “Education Scientific Disciplines,” “Psychology Educational,” and “Education Special.” Some journals may be classified and listed in more than one category, for example, IJSTEM that is listed under both “Education Educational Research” and “Education Scientific Disciplines.” Nevertheless, it is clear that the 2nd search covered more journals and publications with all four categories.

Table 4 shows the list of all journals (50) that published the top 100 most-cited empirical research articles from these two searches, with 43 journals published the top 100 identified in the 1st search and 45 journals in the second search. The vast majority of the journals were the same (38). At the same time, we observed a few important differences. First, there were a few journals (see journal titles in bold in Table 4 , all SSCI journals) likely not listed under “Education Educational Research” but published highly cited empirical research articles in STEM education, especially CBE-Life Science Education (CBE-LSE) and the Journal of Educational Psychology . The inclusion of these new journals from the search actually resulted in significant changes to the allocation of top 100 most-cited empirical research publications in other journals. Moreover, if taking a close look at these nine articles published in CBE-LSE (a journal specified with STEM discipline), we found that these articles were all published more recently from 2014 to 2019, with three in 2014, two in 2015, and one in 2016, 2017, 2018, and 2019, respectively. The result is consistent with a trend we noticed above from Fig.  3 .

Second, some journals (see journal titles in italics in Table 4 ) from the first search being pushed out in the second search, as publications in these journals did not have high enough citations for inclusion as part of the top 100 list. Moreover, these five journals were all on general education research, except one ( Physical Review Physics Education Research ).

Taken together, the results suggest that differences can occur with the use of different categories in the WoS searches. The use of all four categories under “education” would make the search more inclusive, which is what we conducted in the WoS core database search in the recent research review (Li et al., 2022 ).

Concluding Remarks

This study, for the first time, examined trends in highly cited empirical research publications in STEM education, through reviewing the top 100 most-cited journal articles identified from the WoS core database in each of three consecutive years. The systematic analysis of these publications reveals the on-going accumulation and development of STEM education scholarship. Although empirical research in STEM education has been consistently published in many well-established journals especially in educational research, our analysis shows that a growing number of those highly cited research articles were published in journals specified more or less with STEM discipline(s). In particular, among the top 10 journals that published more than 50% of those top 100 most-cited articles in each search, the International Journal of STEM Education was able to make to the top 10 journal list even though it is the only one established after 2000.

Across these three searches, the vast majority of those highly cited research publications focused on multidisciplinary STEM education. At the same time, the lists of publications identified from recent searches in 2021 and 2022 contain no publication on a single discipline of STEM before 2011 but an increasing number of publications on multidisciplinary STEM education in recent years. A trend shows an increased interest and development in recent publications on multi- and interdisciplinary STEM education.

With a restriction on empirical research in STEM education from the WoS database, this study differed from previous research reviews that covered all types of articles on STEM education in different journals (e.g., Li & Xiao, 2022 ; Li et al., 2020 ). Nevertheless, our analysis in this study shows that culture, social, and gender issues in STEM education (TC6) and STEM learner, learning, and learning environments at post-secondary level (TC4) were popular topic areas among those highly cited research publications. In contrast, teaching, teacher, and teacher education in STEM in K-12 education (TC1) and teacher and teaching in STEM at post-secondary level (TC2) were not popular. As research in these TCs has been growing with increased publications (Li & Xiao, 2022 ), we would not be surprised if more publications in these areas will appear in the top 100 research publication list in the future.

It may also be the case that teaching, teachers, and teacher preparation are the focus of already-published research that is still too recent to have accumulated the citations necessary to become highly cited. If one major goal of literature reviews is to help scholars identify promising topics of inquiry, this “lag” time problem suggests that citations—while a helpful proxy—need to be supplemented with other indicators, including those that may not be even dependent on the arduous (and often lengthy) process of getting one’s work published in a journal. A recent review of publications in the International Journal of STEM Education shows the value of using different indicators for publication performance measurements, such as altmetrics (Li, 2022 ). Finding other ways to locate the field’s promising topics will benefit researchers and journals such as ours which can play an important role in providing a platform for sharing and promoting integrated research in STEM education.

Data Availability

The data and materials used and analyzed for the report were obtained through searching the Web of Science database, and related journal information are available directly from these journals’ websites.

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The authors wish to thank Jeff Davis and the staff at Springer for their support in publishing this article.

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YL conceived the study, conducted data analyses, and drafted the manuscript. KW and YX contributed with article search, identification, selection, and coding. SMW reviewed drafts and contributed to manuscript revisions. All authors read and approved the final manuscript.

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Li, Y., Wang, K., Xiao, Y. et al. Trends in Highly Cited Empirical Research in STEM Education: a Literature Review. Journal for STEM Educ Res 5 , 303–321 (2022). https://doi.org/10.1007/s41979-022-00081-7

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200+ Experimental Quantitative Research Topics For STEM Students In 2023

STEM means Science, Technology, Engineering, and Math, which is not the only stuff we learn in school. It is like a treasure chest of skills that help students become great problem solvers, ready to tackle the real world’s challenges.

In this blog, we are here to explore the world of Research Topics for STEM Students. We will break down what STEM really means and why it is so important for students. In addition, we will give you the lowdown on how to pick a fascinating research topic. We will explain a list of 200+ Experimental Quantitative Research Topics For STEM Students.

And when it comes to writing a research title, we will guide you step by step. So, stay with us as we unlock the exciting world of STEM research – it is not just about grades; it is about growing smarter, more confident, and happier along the way.

What Is STEM?

Table of Contents

STEM is Science, Technology, Engineering, and Mathematics. It is a way of talking about things like learning, jobs, and activities related to these four important subjects. Science is about understanding the world around us, technology is about using tools and machines to solve problems, engineering is about designing and building things, and mathematics is about numbers and solving problems with them. STEM helps us explore, discover, and create cool stuff that makes our world better and more exciting.

Why STEM Research Is Important?

STEM research is important because it helps us learn new things about the world and solve problems. When scientists, engineers, and mathematicians study these subjects, they can discover cures for diseases, create new technology that makes life easier, and build things that help us live better. It is like a big puzzle where we put together pieces of knowledge to make our world safer, healthier, and more fun.

• STEM research leads to new discoveries and solutions.
• It helps find cures for diseases.
• STEM technology makes life easier.
• Engineers build things that improve our lives.
• Mathematics helps us understand and solve complex problems.

How to Choose a Topic for STEM Research Paper

Here are some steps to choose a topic for STEM Research Paper:

Step 1: Identify Your Interests

Think about what you like and what excites you in science, technology, engineering, or math. It could be something you learned in school, saw in the news, or experienced in your daily life. Choosing a topic you’re passionate about makes the research process more enjoyable.

Step 2: Research Existing Topics

Look up different STEM research areas online, in books, or at your library. See what scientists and experts are studying. This can give you ideas and help you understand what’s already known in your chosen field.

Step 3: Consider Real-World Problems

Think about the problems you see around you. Are there issues in your community or the world that STEM can help solve? Choosing a topic that addresses a real-world problem can make your research impactful.

Step 4: Talk to Teachers and Mentors

Discuss your interests with your teachers, professors, or mentors. They can offer guidance and suggest topics that align with your skills and goals. They may also provide resources and support for your research.

Step 5: Narrow Down Your Topic

Once you have some ideas, narrow them down to a specific research question or project. Make sure it’s not too broad or too narrow. You want a topic that you can explore in depth within the scope of your research paper.

Here we will discuss 200+ Experimental Quantitative Research Topics For STEM Students: 

Qualitative Research Topics for STEM Students:

Qualitative research focuses on exploring and understanding phenomena through non-numerical data and subjective experiences. Here are 10 qualitative research topics for STEM students:

• Exploring the experiences of female STEM students in overcoming gender bias in academia.
• Understanding the perceptions of teachers regarding the integration of technology in STEM education.
• Investigating the motivations and challenges of STEM educators in underprivileged schools.
• Exploring the attitudes and beliefs of parents towards STEM education for their children.
• Analyzing the impact of collaborative learning on student engagement in STEM subjects.
• Investigating the experiences of STEM professionals in bridging the gap between academia and industry.
• Understanding the cultural factors influencing STEM career choices among minority students.
• Exploring the role of mentorship in the career development of STEM graduates.
• Analyzing the perceptions of students towards the ethics of emerging STEM technologies like AI and CRISPR.
• Investigating the emotional well-being and stress levels of STEM students during their academic journey.

Easy Experimental Research Topics for STEM Students:

These experimental research topics are relatively straightforward and suitable for STEM students who are new to research:

•  Measuring the effect of different light wavelengths on plant growth.
•  Investigating the relationship between exercise and heart rate in various age groups.
•  Testing the effectiveness of different insulating materials in conserving heat.
•  Examining the impact of pH levels on the rate of chemical reactions.
•  Studying the behavior of magnets in different temperature conditions.
•  Investigating the effect of different concentrations of a substance on bacterial growth.
•  Testing the efficiency of various sunscreen brands in blocking UV radiation.
•  Measuring the impact of music genres on concentration and productivity.
•  Examining the correlation between the angle of a ramp and the speed of a rolling object.
•  Investigating the relationship between the number of blades on a wind turbine and energy output.

Research Topics for STEM Students in the Philippines:

These research topics are tailored for STEM students in the Philippines:

•  Assessing the impact of climate change on the biodiversity of coral reefs in the Philippines.
•  Studying the potential of indigenous plants in the Philippines for medicinal purposes.
•  Investigating the feasibility of harnessing renewable energy sources like solar and wind in rural Filipino communities.
•  Analyzing the water quality and pollution levels in major rivers and lakes in the Philippines.
•  Exploring sustainable agricultural practices for small-scale farmers in the Philippines.
•  Assessing the prevalence and impact of dengue fever outbreaks in urban areas of the Philippines.
•  Investigating the challenges and opportunities of STEM education in remote Filipino islands.
•  Studying the impact of typhoons and natural disasters on infrastructure resilience in the Philippines.
•  Analyzing the genetic diversity of endemic species in the Philippine rainforests.
•  Assessing the effectiveness of disaster preparedness programs in Philippine communities.

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Good Research Topics for STEM Students:

These research topics are considered good because they offer interesting avenues for investigation and learning:

•  Developing a low-cost and efficient water purification system for rural communities.
•  Investigating the potential use of CRISPR-Cas9 for gene therapy in genetic disorders.
•  Studying the applications of blockchain technology in securing medical records.
•  Analyzing the impact of 3D printing on customized prosthetics for amputees.
•  Exploring the use of artificial intelligence in predicting and preventing forest fires.
•  Investigating the effects of microplastic pollution on aquatic ecosystems.
•  Analyzing the use of drones in monitoring and managing agricultural crops.
•  Studying the potential of quantum computing in solving complex optimization problems.
•  Investigating the development of biodegradable materials for sustainable packaging.
•  Exploring the ethical implications of gene editing in humans.

Unique Research Topics for STEM Students:

Unique research topics can provide STEM students with the opportunity to explore unconventional and innovative ideas. Here are 10 unique research topics for STEM students:

•  Investigating the use of bioluminescent organisms for sustainable lighting solutions.
•  Studying the potential of using spider silk proteins for advanced materials in engineering.
•  Exploring the application of quantum entanglement for secure communication in the field of cryptography.
•  Analyzing the feasibility of harnessing geothermal energy from underwater volcanoes.
•  Investigating the use of CRISPR-Cas12 for rapid and cost-effective disease diagnostics.
•  Studying the interaction between artificial intelligence and human creativity in art and music generation.
•  Exploring the development of edible packaging materials to reduce plastic waste.
•  Investigating the impact of microgravity on cellular behavior and tissue regeneration in space.
•  Analyzing the potential of using sound waves to detect and combat invasive species in aquatic ecosystems.
•  Studying the use of biotechnology in reviving extinct species, such as the woolly mammoth.

Experimental Research Topics for STEM Students in the Philippines

Research topics for STEM students in the Philippines can address specific regional challenges and opportunities. Here are 10 experimental research topics for STEM students in the Philippines:

•  Assessing the effectiveness of locally sourced materials for disaster-resilient housing construction in typhoon-prone areas.
•  Investigating the utilization of indigenous plants for natural remedies in Filipino traditional medicine.
•  Studying the impact of volcanic soil on crop growth and agriculture in volcanic regions of the Philippines.
•  Analyzing the water quality and purification methods in remote island communities.
•  Exploring the feasibility of using bamboo as a sustainable construction material in the Philippines.
•  Investigating the potential of using solar stills for freshwater production in water-scarce regions.
•  Studying the effects of climate change on the migration patterns of bird species in the Philippines.
•  Analyzing the growth and sustainability of coral reefs in marine protected areas.
•  Investigating the utilization of coconut waste for biofuel production.
•  Studying the biodiversity and conservation efforts in the Tubbataha Reefs Natural Park.

Capstone Research Topics for STEM Students in the Philippines:

Capstone research projects are often more comprehensive and can address real-world issues. Here are 10 capstone research topics for STEM students in the Philippines:

•  Designing a low-cost and sustainable sanitation system for informal settlements in urban Manila.
•  Developing a mobile app for monitoring and reporting natural disasters in the Philippines.
•  Assessing the impact of climate change on the availability and quality of drinking water in Philippine cities.
•  Designing an efficient traffic management system to address congestion in major Filipino cities.
•  Analyzing the health implications of air pollution in densely populated urban areas of the Philippines.
•  Developing a renewable energy microgrid for off-grid communities in the archipelago.
•  Assessing the feasibility of using unmanned aerial vehicles (drones) for agricultural monitoring in rural Philippines.
•  Designing a low-cost and sustainable aquaponics system for urban agriculture.
•  Investigating the potential of vertical farming to address food security in densely populated urban areas.
•  Developing a disaster-resilient housing prototype suitable for typhoon-prone regions.

Experimental Quantitative Research Topics for STEM Students:

Experimental quantitative research involves the collection and analysis of numerical data to conclude. Here are 10 Experimental Quantitative Research Topics For STEM Students interested in experimental quantitative research:

•  Examining the impact of different fertilizers on crop yield in agriculture.
•  Investigating the relationship between exercise and heart rate among different age groups.
•  Analyzing the effect of varying light intensities on photosynthesis in plants.
•  Studying the efficiency of various insulation materials in reducing building heat loss.
•  Investigating the relationship between pH levels and the rate of corrosion in metals.
•  Analyzing the impact of different concentrations of pollutants on aquatic ecosystems.
•  Examining the effectiveness of different antibiotics on bacterial growth.
•  Trying to figure out how temperature affects how thick liquids are.
•  Finding out if there is a link between the amount of pollution in the air and lung illnesses in cities.
•  Analyzing the efficiency of solar panels in converting sunlight into electricity under varying conditions.

Descriptive Research Topics for STEM Students

Descriptive research aims to provide a detailed account or description of a phenomenon. Here are 10 topics for STEM students interested in descriptive research:

•  Describing the physical characteristics and behavior of a newly discovered species of marine life.
•  Documenting the geological features and formations of a particular region.
•  Creating a detailed inventory of plant species in a specific ecosystem.
•  Describing the properties and behavior of a new synthetic polymer.
•  Documenting the daily weather patterns and climate trends in a particular area.
•  Providing a comprehensive analysis of the energy consumption patterns in a city.
•  Describing the structural components and functions of a newly developed medical device.
•  Documenting the characteristics and usage of traditional construction materials in a region.
•  Providing a detailed account of the microbiome in a specific environmental niche.
•  Describing the life cycle and behavior of a rare insect species.

Research Topics for STEM Students in the Pandemic:

The COVID-19 pandemic has raised many research opportunities for STEM students. Here are 10 research topics related to pandemics:

•  Analyzing the effectiveness of various personal protective equipment (PPE) in preventing the spread of respiratory viruses.
•  Studying the impact of lockdown measures on air quality and pollution levels in urban areas.
•  Investigating the psychological effects of quarantine and social isolation on mental health.
•  Analyzing the genomic variation of the SARS-CoV-2 virus and its implications for vaccine development.
•  Studying the efficacy of different disinfection methods on various surfaces.
•  Investigating the role of contact tracing apps in tracking & controlling the spread of infectious diseases.
•  Analyzing the economic impact of the pandemic on different industries and sectors.
•  Studying the effectiveness of remote learning in STEM education during lockdowns.
•  Investigating the social disparities in healthcare access during a pandemic.
• Analyzing the ethical considerations surrounding vaccine distribution and prioritization.

Research Topics for STEM Students Middle School

Research topics for middle school STEM students should be engaging and suitable for their age group. Here are 10 research topics:

• Investigating the growth patterns of different types of mold on various food items.
• Studying the negative effects of music on plant growth and development.
• Analyzing the relationship between the shape of a paper airplane and its flight distance.
• Investigating the properties of different materials in making effective insulators for hot and cold beverages.
• Studying the effect of salt on the buoyancy of different objects in water.
• Analyzing the behavior of magnets when exposed to different temperatures.
• Investigating the factors that affect the rate of ice melting in different environments.
• Studying the impact of color on the absorption of heat by various surfaces.
• Analyzing the growth of crystals in different types of solutions.
• Investigating the effectiveness of different natural repellents against common pests like mosquitoes.

Technology Research Topics for STEM Students

Technology is at the forefront of STEM fields. Here are 10 research topics for STEM students interested in technology:

• Developing and optimizing algorithms for autonomous drone navigation in complex environments.
• Exploring the use of blockchain technology for enhancing the security and transparency of supply chains.
• Investigating the applications of virtual reality (VR) and augmented reality (AR) in medical training and surgery simulations.
• Studying the potential of 3D printing for creating personalized prosthetics and orthopedic implants.
• Analyzing the ethical and privacy implications of facial recognition technology in public spaces.
• Investigating the development of quantum computing algorithms for solving complex optimization problems.
• Explaining the use of machine learning and AI in predicting and mitigating the impact of natural disasters.
• Studying the advancement of brain-computer interfaces for assisting individuals with
• disabilities.
• Analyzing the role of wearable technology in monitoring and improving personal health and wellness.
• Investigating the use of robotics in disaster response and search and rescue operations.

Scientific Research Topics for STEM Students

Scientific research encompasses a wide range of topics. Here are 10 research topics for STEM students focusing on scientific exploration:

• Investigating the behavior of subatomic particles in high-energy particle accelerators.
• Studying the ecological impact of invasive species on native ecosystems.
• Analyzing the genetics of antibiotic resistance in bacteria and its implications for healthcare.
• Exploring the physics of gravitational waves and their detection through advanced interferometry.
• Investigating the neurobiology of memory formation and retention in the human brain.
• Studying the biodiversity and adaptation of extremophiles in harsh environments.
• Analyzing the chemistry of deep-sea hydrothermal vents and their potential for life beyond Earth.
• Exploring the properties of superconductors and their applications in technology.
• Investigating the mechanisms of stem cell differentiation for regenerative medicine.
• Studying the dynamics of climate change and its impact on global ecosystems.

Interesting Research Topics for STEM Students:

Engaging and intriguing research topics can foster a passion for STEM. Here are 10 interesting research topics for STEM students:

• Exploring the science behind the formation of auroras and their cultural significance.
• Investigating the mysteries of dark matter and dark energy in the universe.
• Studying the psychology of decision-making in high-pressure situations, such as sports or
• emergencies.
• Analyzing the impact of social media on interpersonal relationships and mental health.
• Exploring the potential for using genetic modification to create disease-resistant crops.
• Investigating the cognitive processes involved in solving complex puzzles and riddles.
• Studying the history and evolution of cryptography and encryption methods.
• Analyzing the physics of time travel and its theoretical possibilities.
• Exploring the role of Artificial Intelligence  in creating art and music.
• Investigating the science of happiness and well-being, including factors contributing to life satisfaction.

Practical Research Topics for STEM Students

Practical research often leads to real-world solutions. Here are 10 practical research topics for STEM students:

• Developing an affordable and sustainable water purification system for rural communities.
• Designing a low-cost, energy-efficient home heating and cooling system.
• Investigating strategies for reducing food waste in the supply chain and households.
• Studying the effectiveness of eco-friendly pest control methods in agriculture.
• Analyzing the impact of renewable energy integration on the stability of power grids.
• Developing a smartphone app for early detection of common medical conditions.
• Investigating the feasibility of vertical farming for urban food production.
• Designing a system for recycling and upcycling electronic waste.
• Studying the environmental benefits of green roofs and their potential for urban heat island mitigation.
• Analyzing the efficiency of alternative transportation methods in reducing carbon emissions.

Experimental Research Topics for STEM Students About Plants

Plants offer a rich field for experimental research. Here are 10 experimental research topics about plants for STEM students:

• Investigating the effect of different light wavelengths on plant growth and photosynthesis.
• Studying the impact of various fertilizers and nutrient solutions on crop yield.
• Analyzing the response of plants to different types and concentrations of plant hormones.
• Investigating the role of mycorrhizal in enhancing nutrient uptake in plants.
• Studying the effects of drought stress and water scarcity on plant physiology and adaptation mechanisms.
• Analyzing the influence of soil pH on plant nutrient availability and growth.
• Investigating the chemical signaling and defense mechanisms of plants against herbivores.
• Studying the impact of environmental pollutants on plant health and genetic diversity.
• Analyzing the role of plant secondary metabolites in pharmaceutical and agricultural applications.
• Investigating the interactions between plants and beneficial microorganisms in the rhizosphere.

Qualitative Research Topics for STEM Students in the Philippines

Qualitative research in the Philippines can address local issues and cultural contexts. Here are 10 qualitative research topics for STEM students in the Philippines:

• Exploring indigenous knowledge and practices in sustainable agriculture in Filipino communities.
• Studying the perceptions and experiences of Filipino fishermen in coping with climate change impacts.
• Analyzing the cultural significance and traditional uses of medicinal plants in indigenous Filipino communities.
• Investigating the barriers and facilitators of STEM education access in remote Philippine islands.
• Exploring the role of traditional Filipino architecture in natural disaster resilience.
• Studying the impact of indigenous farming methods on soil conservation and fertility.
• Analyzing the cultural and environmental significance of mangroves in coastal Filipino regions.
• Investigating the knowledge and practices of Filipino healers in treating common ailments.
• Exploring the cultural heritage and conservation efforts of the Ifugao rice terraces.
• Studying the perceptions and practices of Filipino communities in preserving marine biodiversity.

Science Research Topics for STEM Students

Science offers a diverse range of research avenues. Here are 10 science research topics for STEM students:

• Investigating the potential of gene editing techniques like CRISPR-Cas9 in curing genetic diseases.
• Studying the ecological impacts of species reintroduction programs on local ecosystems.
• Analyzing the effects of microplastic pollution on aquatic food webs and ecosystems.
• Investigating the link between air pollution and respiratory health in urban populations.
• Studying the role of epigenetics in the inheritance of acquired traits in organisms.
• Analyzing the physiology and adaptations of extremophiles in extreme environments on Earth.
• Investigating the genetics of longevity and factors influencing human lifespan.
• Studying the behavioral ecology and communication strategies of social insects.
• Analyzing the effects of deforestation on global climate patterns and biodiversity loss.
• Investigating the potential of synthetic biology in creating bioengineered organisms for beneficial applications.

Correlational Research Topics for STEM Students

Correlational research focuses on relationships between variables. Here are 10 correlational research topics for STEM students:

• Analyzing the correlation between dietary habits and the incidence of chronic diseases.
• Studying the relationship between exercise frequency and mental health outcomes.
• Investigating the correlation between socioeconomic status and access to quality healthcare.
• Analyzing the link between social media usage and self-esteem in adolescents.
• Studying the correlation between academic performance and sleep duration among students.
• Investigating the relationship between environmental factors and the prevalence of allergies.
• Analyzing the correlation between technology use and attention span in children.
• Studying how environmental factors are related to the frequency of allergies.
• Investigating the link between parental involvement in education and student achievement.
• Analyzing the correlation between temperature fluctuations and wildlife migration patterns.

Quantitative Research Topics for STEM Students in the Philippines

Quantitative research in the Philippines can address specific regional issues. Here are 10 quantitative research topics for STEM students in the Philippines

• Analyzing the impact of typhoons on coastal erosion rates in the Philippines.
• Studying the quantitative effects of land use change on watershed hydrology in Filipino regions.
• Investigating the quantitative relationship between deforestation and habitat loss for endangered species.
• Analyzing the quantitative patterns of marine biodiversity in Philippine coral reef ecosystems.
• Studying the quantitative assessment of water quality in major Philippine rivers and lakes.
• Investigating the quantitative analysis of renewable energy potential in specific Philippine provinces.
• Analyzing the quantitative impacts of agricultural practices on soil health and fertility.
• Studying the quantitative effectiveness of mangrove restoration in coastal protection in the Philippines.
• Investigating the quantitative evaluation of indigenous agricultural practices for sustainability.
• Analyzing the quantitative patterns of air pollution and its health impacts in urban Filipino areas.

Things That Must Keep In Mind While Writing Quantitative Research Title 

Here are few things that must be keep in mind while writing quantitative research tile:

1. Be Clear and Precise

Make sure your research title is clear and says exactly what your study is about. People should easily understand the topic and goals of your research by reading the title.

2. Use Important Words

Include words that are crucial to your research, like the main subjects, who you’re studying, and how you’re doing your research. This helps others find your work and understand what it’s about.

3. Avoid Confusing Words

Stay away from words that might confuse people. Your title should be easy to grasp, even if someone isn’t an expert in your field.

4. Show Your Research Approach

Tell readers what kind of research you did, like experiments or surveys. This gives them a hint about how you conducted your study.

5. Match Your Title with Your Research Questions

Make sure your title matches the questions you’re trying to answer in your research. It should give a sneak peek into what your study is all about and keep you on the right track as you work on it.

STEM students, addressing what STEM is and why research matters in this field. It offered an extensive list of research topics , including experimental, qualitative, and regional options, catering to various academic levels and interests. Whether you’re a middle school student or pursuing advanced studies, these topics offer a wealth of ideas. The key takeaway is to choose a topic that resonates with your passion and aligns with your goals, ensuring a successful journey in STEM research. Choose the best Experimental Quantitative Research Topics For Stem Students today!

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Best 151+ Quantitative Research Topics for STEM Students

In today’s rapidly evolving world, STEM (Science, Technology, Engineering, and Mathematics) fields have gained immense significance. For STEM students, engaging in quantitative research is a pivotal aspect of their academic journey. Quantitative research involves the systematic collection and interpretation of numerical data to address research questions or test hypotheses. Choosing the right research topic is essential to ensure a successful and meaningful research endeavor. 

In this blog, we will explore 151+ quantitative research topics for STEM students. Whether you are an aspiring scientist, engineer, or mathematician, this comprehensive list will inspire your research journey. But we understand that the journey through STEM education and research can be challenging at times. That’s why we’re here to support you every step of the way with our Engineering Assignment Help service. 

What is Quantitative Research in STEM?

Table of Contents

Quantitative research is a scientific approach that relies on numerical data and statistical analysis to draw conclusions and make predictions. In STEM fields, quantitative research encompasses a wide range of methodologies, including experiments, surveys, and data analysis. The key characteristics of quantitative research in STEM include:

• Data Collection: Systematic gathering of numerical data through experiments, observations, or surveys.
• Statistical Analysis: Application of statistical techniques to analyze data and draw meaningful conclusions.
• Hypothesis Testing: Testing hypotheses and theories using quantitative data.
• Replicability: The ability to replicate experiments and obtain consistent results.
• Generalizability: Drawing conclusions that can be applied to larger populations or phenomena.

Importance of Quantitative Research Topics for STEM Students

Quantitative research plays a pivotal role in STEM education and research for several reasons:

1. Empirical Evidence

It provides empirical evidence to support or refute scientific theories and hypotheses.

2. Data-Driven Decision-Making

STEM professionals use quantitative research to make informed decisions, from designing experiments to developing new technologies.

3. Innovation

It fuels innovation by providing data-driven insights that lead to the creation of new products, processes, and technologies.

4. Problem Solving

STEM students learn critical problem-solving skills through quantitative research, which are invaluable in their future careers.

5. Interdisciplinary Applications 

Quantitative research transcends STEM disciplines, facilitating collaboration and the tackling of complex, real-world problems.

Also Read: Google Scholar Research Topics

Quantitative Research Topics for STEM Students

Now, let’s explore important quantitative research topics for STEM students:

Biology and Life Sciences

Here are some quantitative research topics in biology and life science:

1. The impact of climate change on biodiversity.

2. Analyzing the genetic basis of disease susceptibility.

3. Studying the effectiveness of vaccines in preventing infectious diseases.

4. Investigating the ecological consequences of invasive species.

5. Examining the role of genetics in aging.

6. Analyzing the effects of pollution on aquatic ecosystems.

7. Studying the evolution of antibiotic resistance.

8. Investigating the relationship between diet and lifespan.

9. Analyzing the impact of deforestation on wildlife.

10. Studying the genetics of cancer development.

11. Investigating the effectiveness of various plant fertilizers.

12. Analyzing the impact of microplastics on marine life.

13. Studying the genetics of human behavior.

14. Investigating the effects of pollution on plant growth.

15. Analyzing the microbiome’s role in human health.

16. Studying the impact of climate change on crop yields.

17. Investigating the genetics of rare diseases.

Let’s get started with some quantitative research topics for stem students in chemistry:

1. Studying the properties of superconductors at different temperatures.

2. Analyzing the efficiency of various catalysts in chemical reactions.

3. Investigating the synthesis of novel polymers with unique properties.

4. Studying the kinetics of chemical reactions.

5. Analyzing the environmental impact of chemical waste disposal.

6. Investigating the properties of nanomaterials for drug delivery.

7. Studying the behavior of nanoparticles in different solvents.

8. Analyzing the use of renewable energy sources in chemical processes.

9. Investigating the chemistry of atmospheric pollutants.

10. Studying the properties of graphene for electronic applications.

11. Analyzing the use of enzymes in industrial processes.

12. Investigating the chemistry of alternative fuels.

13. Studying the synthesis of pharmaceutical compounds.

14. Analyzing the properties of materials for battery technology.

15. Investigating the chemistry of natural products for drug discovery.

16. Analyzing the effects of chemical additives on food preservation.

17. Investigating the chemistry of carbon capture and utilization technologies.

Here are some quantitative research topics in physics for stem students:

1. Investigating the behavior of subatomic particles in high-energy collisions.

2. Analyzing the properties of dark matter and dark energy.

3. Studying the quantum properties of entangled particles.

4. Investigating the dynamics of black holes and their gravitational effects.

5. Analyzing the behavior of light in different mediums.

6. Studying the properties of superfluids at low temperatures.

7. Investigating the physics of renewable energy sources like solar cells.

8. Analyzing the properties of materials at extreme temperatures and pressures.

9. Studying the behavior of electromagnetic waves in various applications.

10. Investigating the physics of quantum computing.

11. Analyzing the properties of magnetic materials for data storage.

12. Studying the behavior of particles in plasma for fusion energy research.

13. Investigating the physics of nanoscale materials and devices.

14. Analyzing the properties of materials for use in semiconductors.

15. Studying the principles of thermodynamics in energy efficiency.

16. Investigating the physics of gravitational waves.

17. Analyzing the properties of materials for use in quantum technologies.

Engineering

Let’s explore some quantitative research topics for stem students in engineering: 

1. Investigating the efficiency of renewable energy systems in urban environments.

2. Analyzing the impact of 3D printing on manufacturing processes.

3. Studying the structural integrity of materials in aerospace engineering.

4. Investigating the use of artificial intelligence in autonomous vehicles.

5. Analyzing the efficiency of water treatment processes in civil engineering.

6. Studying the impact of robotics in healthcare.

7. Investigating the optimization of supply chain logistics using quantitative methods.

8. Analyzing the energy efficiency of smart buildings.

9. Studying the effects of vibration on structural engineering.

10. Investigating the use of drones in agricultural practices.

11. Analyzing the impact of machine learning in predictive maintenance.

12. Studying the optimization of transportation networks.

13. Investigating the use of nanomaterials in electronic devices.

14. Analyzing the efficiency of renewable energy storage systems.

15. Studying the impact of AI-driven design in architecture.

16. Investigating the optimization of manufacturing processes using Industry 4.0 technologies.

17. Analyzing the use of robotics in underwater exploration.

Environmental Science

Here are some top quantitative research topics in environmental science for students:

1. Investigating the effects of air pollution on respiratory health.

2. Analyzing the impact of deforestation on climate change.

3. Studying the biodiversity of coral reefs and their conservation.

4. Investigating the use of remote sensing in monitoring deforestation.

5. Analyzing the effects of plastic pollution on marine ecosystems.

6. Studying the impact of climate change on glacier retreat.

7. Investigating the use of wetlands for water quality improvement.

8. Analyzing the effects of urbanization on local microclimates.

9. Studying the impact of oil spills on aquatic ecosystems.

10. Investigating the use of renewable energy in mitigating greenhouse gas emissions.

11. Analyzing the effects of soil erosion on agricultural productivity.

12. Studying the impact of invasive species on native ecosystems.

13. Investigating the use of bioremediation for soil cleanup.

14. Analyzing the effects of climate change on migratory bird patterns.

15. Studying the impact of land use changes on water resources.

16. Investigating the use of green infrastructure for urban stormwater management.

17. Analyzing the effects of noise pollution on wildlife behavior.

Computer Science

Let’s get started with some simple quantitative research topics for stem students:

1. Investigating the efficiency of machine learning algorithms for image recognition.

2. Analyzing the security of blockchain technology in financial transactions.

3. Studying the impact of quantum computing on cryptography.

4. Investigating the use of natural language processing in chatbots and virtual assistants.

5. Analyzing the effectiveness of cybersecurity measures in protecting sensitive data.

6. Studying the impact of algorithmic trading in financial markets.

7. Investigating the use of deep learning in autonomous robotics.

8. Analyzing the efficiency of data compression algorithms for large datasets.

9. Studying the impact of virtual reality in medical simulations.

10. Investigating the use of artificial intelligence in personalized medicine.

11. Analyzing the effectiveness of recommendation systems in e-commerce.

12. Studying the impact of cloud computing on data storage and processing.

13. Investigating the use of neural networks in predicting disease outbreaks.

14. Analyzing the efficiency of data mining techniques in customer behavior analysis.

15. Studying the impact of social media algorithms on user behavior.

16. Investigating the use of machine learning in natural language translation.

17. Analyzing the effectiveness of sentiment analysis in social media monitoring.

Mathematics

Let’s explore the quantitative research topics in mathematics for students:

1. Investigating the properties of prime numbers and their distribution.

2. Analyzing the behavior of chaotic systems using differential equations.

3. Studying the optimization of algorithms for solving complex mathematical problems.

4. Investigating the use of graph theory in network analysis.

5. Analyzing the properties of fractals in natural phenomena.

6. Studying the application of probability theory in risk assessment.

7. Investigating the use of numerical methods in solving partial differential equations.

8. Analyzing the properties of mathematical models for population dynamics.

9. Studying the optimization of algorithms for data compression.

10. Investigating the use of topology in data analysis.

11. Analyzing the behavior of mathematical models in financial markets.

12. Studying the application of game theory in strategic decision-making.

13. Investigating the use of mathematical modeling in epidemiology.

14. Analyzing the properties of algebraic structures in coding theory.

15. Studying the optimization of algorithms for image processing.

16. Investigating the use of number theory in cryptography.

17. Analyzing the behavior of mathematical models in climate prediction.

Earth Sciences

Here are some quantitative research topics for stem students in earth science:

1. Investigating the impact of volcanic eruptions on climate patterns.

2. Analyzing the behavior of earthquakes along tectonic plate boundaries.

3. Studying the geomorphology of river systems and erosion.

4. Investigating the use of remote sensing in monitoring wildfires.

5. Analyzing the effects of glacier melt on sea-level rise.

6. Studying the impact of ocean currents on weather patterns.

7. Investigating the use of geothermal energy in renewable power generation.

8. Analyzing the behavior of tsunamis and their destructive potential.

9. Studying the impact of soil erosion on agricultural productivity.

10. Investigating the use of geological data in mineral resource exploration.

11. Analyzing the effects of climate change on coastal erosion.

12. Studying the geomagnetic field and its role in navigation.

13. Investigating the use of radar technology in weather forecasting.

14. Analyzing the behavior of landslides and their triggers.

15. Studying the impact of groundwater depletion on aquifer systems.

16. Investigating the use of GIS (Geographic Information Systems) in land-use planning.

17. Analyzing the effects of urbanization on heat island formation.

Health Sciences and Medicine

Here are some quantitative research topics for stem students in health science and medicine:

1. Investigating the effectiveness of telemedicine in improving healthcare access.

2. Analyzing the impact of personalized medicine in cancer treatment.

3. Studying the epidemiology of infectious diseases and their spread.

4. Investigating the use of wearable devices in monitoring patient health.

5. Analyzing the effects of nutrition and exercise on metabolic health.

6. Studying the impact of genetics in predicting disease susceptibility.

7. Investigating the use of artificial intelligence in medical diagnosis.

8. Analyzing the behavior of pharmaceutical drugs in clinical trials.

9. Studying the effectiveness of mental health interventions in schools.

10. Investigating the use of gene editing technologies in treating genetic disorders.

11. Analyzing the properties of medical imaging techniques for early disease detection.

12. Studying the impact of vaccination campaigns on public health.

13. Investigating the use of regenerative medicine in tissue repair.

14. Analyzing the behavior of pathogens in antimicrobial resistance.

15. Studying the epidemiology of chronic diseases like diabetes and heart disease.

16. Investigating the use of bioinformatics in genomics research.

17. Analyzing the effects of environmental factors on health outcomes.

Quantitative research is the backbone of STEM fields, providing the tools and methodologies needed to explore, understand, and innovate in the world of science and technology . As STEM students, embracing quantitative research not only enhances your analytical skills but also equips you to address complex real-world challenges. With the extensive list of 155+ quantitative research topics for stem students provided in this blog, you have a starting point for your own STEM research journey. Whether you’re interested in biology, chemistry, physics, engineering, or any other STEM discipline, there’s a wealth of quantitative research topics waiting to be explored. So, roll up your sleeves, grab your lab coat or laptop, and embark on your quest for knowledge and discovery in the exciting world of STEM.

I hope you enjoyed this blog post about quantitative research topics for stem students.

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55 Brilliant Research Topics For STEM Students

Primarily, STEM is an acronym for Science, Technology, Engineering, and Mathematics. It’s a study program that weaves all four disciplines for cross-disciplinary knowledge to solve scientific problems. STEM touches across a broad array of subjects as STEM students are required to gain mastery of four disciplines.

As a project-based discipline, STEM has different stages of learning. The program operates like other disciplines, and as such, STEM students embrace knowledge depending on their level. Since it’s a discipline centered around innovation, students undertake projects regularly. As a STEM student, your project could either be to build or write on a subject. Your first plan of action is choosing a topic if it’s written. After selecting a topic, you’ll need to determine how long a thesis statement should be .

Given that topic is essential to writing any project, this article focuses on research topics for STEM students. So, if you’re writing a STEM research paper or write my research paper , below are some of the best research topics for STEM students.

List of Research Topics For STEM Students

Quantitative research topics for stem students, qualitative research topics for stem students, what are the best experimental research topics for stem students, non-experimental research topics for stem students, capstone research topics for stem students, correlational research topics for stem students, scientific research topics for stem students, simple research topics for stem students, top 10 research topics for stem students, experimental research topics for stem students about plants, research topics for grade 11 stem students, research topics for grade 12 stem students, quantitative research topics for stem high school students, survey research topics for stem students, interesting and informative research topics for senior high school stem students.

Several research topics can be formulated in this field. They cut across STEM science, engineering, technology, and math. Here is a list of good research topics for STEM students.

• The effectiveness of online learning over physical learning
• The rise of metabolic diseases and their relationship to increased consumption
• How immunotherapy can improve prognosis in Covid-19 progression

For your quantitative research in STEM, you’ll need to learn how to cite a thesis MLA for the topic you’re choosing. Below are some of the best quantitative research topics for STEM students.

• A study of the effect of digital technology on millennials
• A futuristic study of a world ruled by robotics
• A critical evaluation of the future demand in artificial intelligence

There are several practical research topics for STEM students. However, if you’re looking for qualitative research topics for STEM students, here are topics to explore.

• An exploration into how microbial factories result in the cause shortage in raw metals
• An experimental study on the possibility of older-aged men passing genetic abnormalities to children
• A critical evaluation of how genetics could be used to help humans live healthier and longer.

Experimental research in STEM is a scientific research methodology that uses two sets of variables. They are dependent and independent variables that are studied under experimental research. Experimental research topics in STEM look into areas of science that use data to derive results.

Below are easy experimental research topics for STEM students.

• A study of nuclear fusion and fission
• An evaluation of the major drawbacks of Biotechnology in the pharmaceutical industry
• A study of single-cell organisms and how they’re capable of becoming an intermediary host for diseases causing bacteria

Unlike experimental research, non-experimental research lacks the interference of an independent variable. Non-experimental research instead measures variables as they naturally occur. Below are some non-experimental quantitative research topics for STEM students.

• Impacts of alcohol addiction on the psychological life of humans
• The popularity of depression and schizophrenia amongst the pediatric population
• The impact of breastfeeding on the child’s health and development

STEM learning and knowledge grow in stages. The older students get, the more stringent requirements are for their STEM research topic. There are several capstone topics for research for STEM students .

Below are some simple quantitative research topics for stem students.

• How population impacts energy-saving strategies
• The application of an Excel table processor capabilities for cost calculation
•  A study of the essence of science as a sphere of human activity

Correlations research is research where the researcher measures two continuous variables. This is done with little or no attempt to control extraneous variables but to assess the relationship. Here are some sample research topics for STEM students to look into bearing in mind how to cite a thesis APA style for your project.

• Can pancreatic gland transplantation cure diabetes?
• A study of improved living conditions and obesity
• An evaluation of the digital currency as a valid form of payment and its impact on banking and economy

There are several science research topics for STEM students. Below are some possible quantitative research topics for STEM students.

• A study of protease inhibitor and how it operates
• A study of how men’s exercise impacts DNA traits passed to children
• A study of the future of commercial space flight

If you’re looking for a simple research topic, below are easy research topics for STEM students.

• How can the problem of Space junk be solved?
• Can meteorites change our view of the universe?
• Can private space flight companies change the future of space exploration?

For your top 10 research topics for STEM students, here are interesting topics for STEM students to consider.

• A comparative study of social media addiction and adverse depression
• The human effect of the illegal use of formalin in milk and food preservation
• An evaluation of the human impact on the biosphere and its results
• A study of how fungus affects plant growth
• A comparative study of antiviral drugs and vaccine
• A study of the ways technology has improved medicine and life science
• The effectiveness of Vitamin D among older adults for disease prevention
• What is the possibility of life on other planets?
• Effects of Hubble Space Telescope on the universe
• A study of important trends in medicinal chemistry research

Below are possible research topics for STEM students about plants:

• How do magnetic fields impact plant growth?
• Do the different colors of light impact the rate of photosynthesis?
• How can fertilizer extend plant life during a drought?

Below are some examples of quantitative research topics for STEM students in grade 11.

• A study of how plants conduct electricity
• How does water salinity affect plant growth?
• A study of soil pH levels on plants

Here are some of the best qualitative research topics for STEM students in grade 12.

• An evaluation of artificial gravity and how it impacts seed germination
• An exploration of the steps taken to develop the Covid-19 vaccine
• Personalized medicine and the wave of the future

Here are topics to consider for your STEM-related research topics for high school students.

• A study of stem cell treatment
• How can molecular biological research of rare genetic disorders help understand cancer?
• How Covid-19 affects people with digestive problems

Below are some survey topics for qualitative research for stem students.

• How does Covid-19 impact immune-compromised people?
• Soil temperature and how it affects root growth
• Burned soil and how it affects seed germination

Here are some descriptive research topics for STEM students in senior high.

• The scientific information concept and its role in conducting scientific research
• The role of mathematical statistics in scientific research
• A study of the natural resources contained in oceans

Final Words About Research Topics For STEM Students

STEM topics cover areas in various scientific fields, mathematics, engineering, and technology. While it can be tasking, reducing the task starts with choosing a favorable topic. If you require external assistance in writing your STEM research, you can seek professional help from our experts.

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• Open access
• Published: 16 May 2018

A study of the correlation between STEM career knowledge, mathematics self-efficacy, career interests, and career activities on the likelihood of pursuing a STEM career among middle school students

• Karen A. Blotnicky 1 ,
• Tamara Franz-Odendaal 2 ,
• Frederick French 3 &
• Phillip Joy 4  

International Journal of STEM Education volume  5 , Article number:  22 ( 2018 ) Cite this article

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A sample of 1448 students in grades 7 and 9 was drawn from public schools in Atlantic Canada to explore students’ knowledge of science and mathematics requirements for science, technology, engineering, and mathematics (STEM) careers. Also explored were their mathematics self-efficacy (MSE), their future career interests, their preferences for particular career activities, and their likelihood to pursue a STEM career.

Analysis revealed that while older students had more knowledge about mathematics/science requirements for STEM careers, this knowledge was lacking overall. Also, students with higher MSE were more knowledgeable about STEM career requirements. Furthermore, students with higher MSE and STEM career knowledge were more likely to choose a STEM career. Students with greater interest in technical and scientific skills were also more likely to consider a STEM career than those who preferred career activities that involved practical, productive, and concrete activities.

Conclusions

The results of this study show that students in middle school have a limited STEM career knowledge with respect to subject requirements and with respect to what sort of activities these careers involve. Furthermore, students with low MSE have a declining interest in STEM careers. Our data thus support the need to improve access to knowledge to facilitate students’ understanding of STEM careers and the nature of STEM work. Exposure of students to STEM careers can enhance their interest in pursuing careers involving science, technology, engineering, and mathematics.

Globally, youth vary considerably in their level of science, technology, engineering, and mathematics (STEM) career knowledge, their career interests, and their intentions of pursuing a STEM career. STEM career knowledge, defined as a student’s familiarity with a particular STEM career, varies considerably based on the school’s STEM career guidance. The level of STEM career knowledge an individual has will directly affect one’s intentions of pursuing a STEM career in the future (Compeau 2016 ; Nugent et al. 2015 ; Zhang and Barnett 2015 ). Without adequate knowledge, there is a risk that students will dismiss a STEM-based career path as a potential option for their future. Consequently, student interest in a particular STEM career will wane, which will negatively influence their desire to participate in activities that serve to increase STEM career knowledge and awareness. Indeed, interventions have shown that equipping students with STEM career knowledge early increases their motivation to take more science and mathematics courses in high school (Harackiewicz et al. 2012 ).

Students’ career interest and their preferred future career activities will also affect their intention of pursuing a STEM career. A key predictor of STEM career interest at the end of high school is interest at the start of high school (Sadler et al. 2012 ). However, the positive attitudes towards science identified in youth age 10 sharply declines by age 14 (Murphy and Beggs 2005 ; Tai et al. 2006 ); the junior high school years are typically ages 12–14 years. An extensive study in 2015, surveying 24,000 students, showed that occupational intentions change dramatically between the 9th and 11th grade and that the relationship between STEM intention and motivation is highly time-sensitive (Mangu et al. 2015 ).

Both STEM career knowledge and career interests are also influenced by society at large. These society influencers include role models that students are exposed to either in person or through the media, the individual students interact with on a daily basis such as teachers, family members, and peers, as well as students’ extracurricular experiences (Dabney et al. 2012 ; Harackiewicz et al. 2012 ; Nugent et al. 2015 ; Sahin et al. 2014 ; Sahin et al. 2015 ; Schumacher et al. 2009 ; Sjaastad 2012 ; Steinke et al. 2009 ; Zhang and Barnett 2015 ). Collectively, these influencing factors predict the self-efficacy (i.e., one’s belief in one’s ability) youth hold about their career options as well as their outcome expectancies (Mangu et al. 2015 ). Self-efficacy is considered a major predictor guiding the selection of majors during high school and post-secondary education (Heilbronner 2009 ; Kelly et al. 2013 ).

The grades 7 through 9 years (12–15-year-olds) are the key time period for influencing STEM career interest and for building this self-efficacy with respect to mathematics and science. Thus, it is during the junior high (middle) school age that a student’s beliefs about competency and interests begin to solidify (Simpkins et al. 2006 ). It is at this time that student engagement activities and career knowledge should be at its highest. Social cognitive career theory (Lent 2005 ) acknowledges and hypothesizes that career interests, choice, and personal goals form a complex human agency process that includes performance, self-efficacy, and outcome expectations. For example, self-efficacy is positively related to student academic performance and science self-efficacy has been shown to impact student selection of science-related activities, which impacts their ultimate success and helps maintain interests (Britner and Pajares 2006 ; Parker et al. 2014 ; Richardson et al. 2012 ).

Early interest in STEM topics is an excellent predictor for later learning and eventual career interests and choice (DeBacker and Nelson 1999 ). Contextual and individual variables influence these social cognitive variables including factors such as parental, teacher, and peer cultural expectations (Lent et al. 1994 ). Nugent et al. ( 2015 ) found support for the social cognitive career theory (Lent et al. 1994 ) as a framework for examining STEM learning and career orientation outcomes by providing a way in which to view the socio-contextual, motivational, and instructional factors that can impact youth STEM interests.

Although 88% of parents believe they can help guide their children’s learning, less than 28% actually discuss the value of a STEM education with their children (“Let’s Talk Science Canada Annual Report,” 2015 ). Recent studies have also indicated that junior high students have an unclear view about engineering (Compeau 2016 ; Karatas et al. 2011 ) and science (Masnick et al. 2010 ) yet these are critical years in which to build STEM interest. The present paper builds on our previous study (Franz-Odendaal et al. 2016 ) and explores students’ knowledge of STEM career mathematics/science requirements and their mathematics self-efficacy (MSE) and how these shape students’ career interests and preferred career activities. Differences among grade 7 and 9 students with respect to career interests and activities, and the likelihood of pursuing a STEM career will be examined. While gender differences are important because STEM stereotypes are heavily biased towards males, these differences are beyond the scope of the current study. This study will examine who, what, and how youth are influenced in STEM career choice.

This study captured five main areas of interest: student knowledge of mathematics and science requirements that lead to STEM careers, MSE, career interests, career activity preferences, and their correlation with the likelihood to consider pursuing a STEM career among youth. Based on the literature, the following research questions were developed to guide this research.

RQ1: What is the correlation between grade level and students’ knowledge of high school requirements for STEM careers?

RQ2: What is the correlation between MSE and students’ knowledge of high school requirements for STEM careers?

RQ3: What is the correlation between MSE and students’ career interests and/or their preference for particular career activities?

RQ4: What is the association between student preferences for career interests and preferred career activities with grade level?

RQ5: What are the relationships between the following factors and the likelihood that students will choose a STEM career: grade level, MSE, student knowledge of mathematics/science requirements for post-secondary study for STEM careers, career interests and preferred career activities?

These research questions have not been explored in the context of Atlantic Canada, thus making this study relevant to the education system within Canada and globally.

Grade 7 and 9 students in the four Canadian Atlantic provinces (New Brunswick, Nova Scotia, Prince Edward Island, and Newfoundland) completed an online survey during their school hours. This research was approved by the university research ethics board. Permission to collect data in the schools was obtained from school board superintendents and parents. Schools were purposefully chosen from school families in geographic areas across Atlantic Canada. English and French language schools were included in the study. Data were weighted to ensure that the sample was representative by grade level, from each of the four Atlantic provinces. A total sample size of 1448 students was obtained across all four provinces in Atlantic Canada: New Brunswick (33%), Nova Scotia (38.4%), Prince Edward Island (6.5%), and Newfoundland-Labrador (22.1%). The sample was split almost evenly between grade 7 (48%) and grade 9 (52%). The sample was balanced with respect to gender (58% female to 42% male). Students ranged in age from 11 to 20 years with an average age of 13.5 years and a median age of 14 years (SD = 1.1). Grade 7 students had an average age of 12.6 years (SD = .6) with a median age of 13 years. Grade 9 students had an average age of 14.5 years (SD = .6) with a median age of 14 years.

Five different measures were used in this study. These included measures of STEM career knowledge, MSE, career activity preferences, career interests, and likelihood to choose to pursue a STEM career. These measures were incorporated into the study based on earlier reviews that found that studies’ examining factors influencing career choice have been criticized for failing to account for the complexity of career choices and career decision-making (Patton and McMahon 2006 ) and for being too static in their view of career development (Hirshi 2011 ).

STEM career knowledge score

A STEM career knowledge (SCK) score was created to capture students’ knowledge about the requirements for high school mathematics and science in STEM careers. Students were presented with 12 STEM careers and asked to indicate whether they believed that the training for each of the careers required having taken mathematics or science in high school. Students could respond “yes” if they believed the career required high school mathematics or science based on their knowledge of the entrance requirements for Canadian colleges and universities. They could respond “no” if they believed that the career did not require high school mathematics or science, or they could choose “uncertain” if they were not sure that high school mathematics and/or science were required for that career. The list included careers students are commonly exposed to (such as veterinarian, pharmacist, and oral hygienist) as well as careers that are likely less familiar to them (such as mechanical engineer, geologist, and land surveyor). The list included mechanical engineer, computer hardware designer, pharmacist, medical technologist, geologist, veterinarian, oil industry engineer, physiotherapist, oral hygienist, nutritionist, land surveyor, and ophthalmologist. The list was provided to students in no particular order.

A score was calculated to capture students’ knowledge based on these responses. “Yes” responses were scored as “1,” “uncertain” responses as “0,” and “no” scored as “− 1.” The responses were then summed to obtain a basic SCK score per student. The SCK score was calculated only for students who had rated at least one third of the careers in the list. The SCK was validated using confirmatory factor analysis (CFA) and reliability analysis.

Mathematics Self-Efficacy Scale

In an attempt to offer a more complete perspective on the process of career decision-making, Hackett and Bertz (Hackett and Betz 1981 ) drew on the work of Bandura ( 1977 ) to introduce the concept of self-efficacy to the career development literature noting its potential to help understand the complexity of career decision-making such as the underrepresentation of women in traditional male-dominated career fields. Self-efficacy referred to the belief that a person had in their own ability to successfully perform a particular behavior based on their perception of their capability and the likelihood of their achieving success in that activity.

The second measure used in this analysis was a MSE scale. Students were asked to describe their experiences in mathematics by rating each of the following statements on a scale ranging from (1) Strongly disagree to (5) Strongly agree: I get good grades in mathematics; I learn quickly in mathematics; I look forward to my mathematics class; I feel tense doing mathematics problems; I feel helpless doing mathematics problems. Negatively phrased items were reverse-coded to maintain consistency in the MSE scale. Students’ responses to these five statements about their experiences in mathematics were then coded into dichotomies to create five separate measures. Dichotomies were created by assigning a value of “1” to those who were most comfortable with Likert scale ratings of 4 or 5 to the statements and assigning a value of 0 to those who were less confident and comfortable with Likert scale ratings of 1 through 3. These five measures were then summed to get a single MSE scale that would reflect higher measures for those who were the most confident and comfortable with mathematics. The MSE scale was validated using confirmatory factor analysis (CFA) and reliability analysis. The resulting MSE score ranged from 0 to 5. The MSE scale was then divided into two subgroups to create an MSE score for further analysis. The MSE score consisted of those with low MSE (scores of 0 through 3) and high MSE (scores of 4 or 5). The goal in using this breakout was to identify students who were the most comfortable and confident in their mathematics experiences.

Career activities and career interests

Social Cognitive Career Theory (SCCT) (Lent et al. 2010 ) has continued to evolve to include person and environmental and socio-demographic variables as well as interest and career choice models. The SCCT argues that people develop interests (actively likes and dislikes) largely on the basis of their beliefs about their self-efficacy and the outcomes their efforts could achieve. Ultimately, people become interested in activities they believe they can perform well. Therefore, people develop goals to pursue academic and career activities that are consistent with their interests as well as with their self-efficacy and outcome expectations (Sheu et al. 2010 ). Thus, career activities and career interests are highly correlated. For these reasons, student ratings of self-perceptions of their career interests, and also their career activities, were included.

The SCCT has been found to support self-efficacy and outcome expectations as significant predictors of interest, that interests partially mediate the relation of self-efficacy and outcome expectations, and that self-efficacy relates to outcome expectations across Holland’s (1997) broad occupational themes as utilized in the current study (Sheu et al. 2010 ). This alignment was felt to provide a rationale for the use of student ratings of interests, activities, and Holland’s broad occupational themes as a comprehensive way of gaining insight into the complexity of career decision-making of junior high students.

Hollands’ Theory of Career Choice and Development (Holland 1973 ) focused on six basic personality types: realistic (practical); investigative (analytical, curious); artistic (expressive, original); social (working/helping others); enterprising (goal oriented); and conventional (ordered). Individuals are not limited to one personality type and many exhibit characteristics on more than one type. Holland ( 1973 ) argued that everyone has career decisions to make at various stages of their lives. As well, he argued that everyone can serve as both a coach and/or a player in those decisions depending on their role, situation, and knowledge. Reflecting on the life stage, the environment, and the knowledge one has of their own particular type of preferred approach to life plus knowledge of the interaction among a variety of factors such as the cultural, social, academic, and family influences on the decisions that each individual makes about their life career. These are not perfect, single, nor static events and depend on self and other perceptions of a wide range of factors. However, at a point in time, they represent what each person conceptualizes as a satisfying career for them. Holland ( 1973 ) argued that his theory of careers was really intended to help practitioners, researchers, and students in education and social science to address a fuller understanding of vocational choice and to be helpful in professional counseling. Miller ( 1998 ) stated that Holland’s theory can be used to help individuals explore career choices. More recently, Olitsky ( 2014 ) used Holland’s theory of career and educational choice when researching the earnings of STEM majors, indicating that the underlying theory is still relevant. Since career interests and career activities are highly correlated, they were measured separately.

The third measure used in this analysis was a ranking of the preferred career activities using Holland’s Theory of Career Choice and Development (1973). Students were asked to rank six different career activities from (1) Most favorite to (6) Least favorite. Each of the career activities was then analyzed based on the percentage of students who rated it in their top 2 favorites. The career activities studied in this research included the following: (1) artistic, unusual, and creative activities; (2) working on practical, productive, and concrete activities; (3) taking responsibility, providing leadership, and convincing others; (4) things being organized into routines and having an order; (5) learning by reading, study, analysis, or investigation; (6) helping others and being concerned for the welfare of others.

The fourth measure used in this analysis was a ranking of career interests also based on Holland’s Theory of Career Choice and Development (Holland 1973 ). Students were asked to rank six different career interests from (1) Most favorite to (6) Least favorite. Each of the career interests was then analyzed based on the percentage of students who rated it in their top 2 favorites. These interests were (1) working with people; (2) creative skills and expression; (3) technical and scientific skills; (4) manual and mechanical skills; (5) leading, persuading, and directing others; and (6) routines and adhering to standards of performance.

Likelihood to pursue a STEM career

The final measure used in this analysis was the likelihood that students would consider choosing a STEM career in their future. Students were asked how likely they would be to choose a career that is science-related (including science, engineering, health, or technology). Likelihood was measured using the following Likert scale: (1) Very unlikely, (2) Somewhat unlikely, (3) Somewhat likely, and (4) Very likely. This scale was recoded into a dichotomous variable for use in bivariate logistic regression: Students who were somewhat likely or very likely to choose a STEM career were coded as “1,” and those who were somewhat unlikely or very unlikely to choose a STEM career were coded as “0.”

Data analysis

Data were analyzed using the SPSS software (IBM Corp 2013 ). Descriptive statistics were used to provide an overall analysis of the data. Various statistical tests were selected based on the level of data measurement and data distributions (McDaniel et al. 2014 ; Hair Jr. et al. 2010 ). t tests were used to explore differences in average ratings between groups. Chi-square was used to analyze associations between nominal and ordinal variables. Analysis of variance (ANOVA) was used to evaluate significant differences between average ratings and measures involving categorical variables with more than two response levels (McDaniel et al. 2014 ). Logistic regression was used to explore research questions involving interval and ratio-scaled variables (Hair Jr. et al. 2010 ). Brown-Forsyth exact tests were used with ANOVA to compensate for violations of homogeneity of variance (IBM Corp 2013 ). Bonferroni post hoc tests were used to detect significant differences between groups for significant ANOVA results (IBM Corp 2013 ; Hair Jr. et al. 2010 ). Data were weighted to reflect the population of students by grade level and province across Atlantic Canada.

Bivariate logistic regression was conducted to explore the relative contribution of the following factors on the likelihood that students would choose a STEM career: SCK score, MSE score, grade level, career interests, and career activities. Grade level, career interest, and career activities were coded as dichotomies for the regression analysis as follows: grade level (grade 9 = 1, grade 7 = 0), career interests (rated in top 2 favorites = 1, not rated in top 2 favorites = 0), career activities (rated in top 2 favorites = 1, not rated in top 2 favorites = 0).

Three regressions were created to explore the research questions. The first analysis regressed grade level, SCK score, and MSE score against the likelihood to pursue a STEM career. Two more regressions were conducted: one to regress career activities and a second to regress career interests against the likelihood to pursue a STEM career as a dependent variable. Measures for career activity and career interests showed a high level of multicollinearity between the two sets of variables. Separating these predictors into two different regressions eliminated problems with multicollinearity.

We first describe the results for each of the measures used in this study and then answer our research questions (RQ1–5).

Student knowledge of mathematics and science requirements for STEM careers

We assessed student’s knowledge of high school requirements for STEM careers, by asking students to indicate whether a career required mathematics and/or science (Table  1 ). Mechanical engineer was noted by 71.4% of students as having a high school mathematics/science requirement. Two careers (land surveyor and ophthalmologist) were noted by less than half of the students as requiring high school mathematics or science. Five careers were classified as requiring mathematics and science by 65.6 to 68.2% (veterinarian, geologist, medical technologist, pharmacist, computer hardware engineer). Four of the careers were listed as requiring mathematics and science by 51.8 to 58.6% of the students (nutritionist, oral hygienist, physiotherapist, oil industry engineer). What is notable in the students’ responses are that most students seemed confident of their career classification in that they answered “yes” or “no” and not the option of “uncertain,” indicating that they were confident in their choice. The percentage of students saying that they were uncertain if a career required mathematics or science for post-secondary study was low and ranged from 12.5 to 32.6% across all of the careers with half of the uncertain responses ranging from 12.5 to 13% of students. Table  1 shows the results of high school mathematics/science requirements for STEM careers.

Students’ responses were summed to obtain an overall SCK score. A factor analysis of the career ratings was used to ensure it was unidimensional, and reliability of the score was measured using Cronbach’s alpha. The confirmatory factor analysis was statistically significant (KMO = .961, p  < .01). Cronbach’s alpha was .95 which meets the criterion for reliability.

The SCK score ranged from − 12 to + 12, with an average score of 4.6 (SD = 7.6; Fig.  1 ). The average SCK score was low, indicating a lack of familiarity with the mathematics and/or science requirements of STEM careers. Approximately 8% of students did not correctly classify any of the careers as having a high school mathematics and/or science requirement. Only 36.4% of students had high SCK scores having correctly classified 10 to 12 careers. The top quartile of students scored 11 or better while the bottom quartile scored 0 or less than 0 out of the 12-point score. A summary of the SCK score is in Fig.  1 .

STEM career knowledge (SCK) score

Overall, these results suggest that STEM career knowledge is limited among middle school students. Results also reveal that students seem to be unaware of their limited knowledge regarding STEM career preparation.

Students’ mathematics self-efficacy

In order to determine whether MSE was correlated with students STEM career knowledge (RQ2) and/or between MSE and career interests and/or preferred career activities (RQ3), we first determined the MSE scale for the cohort. The MSE scale ranged from 0 (No self-efficacy) to 5 (High self-efficacy). The distribution of the Math Self-Efficacy Scale is shown in Fig.  2 .

Mathematics Self-Efficacy (MSE) Scale

A confirmatory factor analysis of the measures in the MSE scale indicated that it was unidimensional and reliable. The factor analysis was statistically significant (KMO = .698, p  < .01). Cronbach’s alpha was .72 which is acceptable for a scale analysis. These results suggest that over half of the students had a relatively high MSE and about one third of students had low MSE.

Career activities and interests

In order to assess students’ preferred career activities and their career interests, students were asked to select their favorites. Students were presented with a list of six career activities and asked to indicate which activities were in their top 2 favorites. These measures were recoded into dichotomies for further analysis. There was a very even spread of students rating career activities in their top 2 favorites, ranging from 32.1 to 45.9%. Most of the activities were listed in their top 2 favorites by about one third of the students. The results revealed that artistic, unusual, and creative activities were most commonly listed in the top 2 favorite career activities. The career activity with the lowest rating was helping others and being concerned for their welfare. The results are summarized in Table  2 .

Students were also presented with a list of six career interests and asked to indicate which career interests were in their top 2 favorites. These measures were recoded into dichotomies for further analysis. The percentage of students rating career interests as their top 2 favorites ranged from 21.9% for routines and adhering to standards to working with people at 49.8%. The results are summarized in Table  3 .

Likelihood of choosing a STEM career

Next, we assessed whether students were interested in pursuing a STEM career. Nearly 70% percent of students surveyed revealed that they were either somewhat likely or very likely to pursue a STEM career. On a scale of (1) Very unlikely to (4) Very likely, an average rating of 2.9/4 indicated that students were somewhat likely to pursue a STEM career. The results appear in Table  4 .

The association of grade level and STEM career knowledge

The first research question (RQ1) explored the correlation of grade level and STEM career knowledge. There was a statistically significant difference in the average SCK score by grade, with grade 9 students scoring higher than grade 7 students (5.7 vs 3.3, t  = − 5.69, df = 1209.7, p  < .01). While it is good to see that students appear to acquire more knowledge of STEM career requirements in middle school grades, it is concerning that students in grade 9 still had a low average SCK score since this is the year in which students begin to choose subject classes in Atlantic Canada. This indicates that more work is needed to ensure students have the correct information about STEM career requirements in time for them to make informed decisions about high school course selection.

Correlation between mathematics self-efficacy and the STEM career knowledge

The second research question (RQ2) focused on whether there is a correlation between students with higher MSE and knowledge of STEM career requirements. An analysis of variance revealed that students with high self-efficacy (MSE scale = 4 and 5) had significantly higher SCK scores than students who did not score as highly in the MSE scale (BF = 8.7, df = 5, p  < .01). Students with high MSE had a SCK score of 6.6 out of 12, while students with lower MSE scores had average SCK scores ranging from 2.8 to 4.8. The results are shown in Table  5 .

These results for RQ2 show that students who report more confidence and comfort in mathematics tend to be more knowledgeable about mathematics/science requirements for STEM careers. This is a correlation only and cannot be interpreted as a causal relationship since survey data cannot be used to measure causality.

Correlation between mathematics self-efficacy and students’ preferred career activities and their career interests

Our third research question (RQ3) explored whether there was a correlation between MSE and students’ career interests and preferred career activity. There were statistically significant differences by students’ preferred career activities for the MSE scale. MSE scale totals were sorted into two groups to create an MSE score for further analysis. Those with low MSE scale totals (0 through 3) were assigned an MSE score of 0, and those with high MSE scale totals (4 and 5) were assigned an MSE score of 1. A chi-square analysis revealed that only one career activity differed significantly based on students’ MSE scores. Reading, study, analysis, and investigation was listed in the top 2 favorites for career activities by 36.5% of students who had high MSE scores (between 4 and 5) when compared to 28.4% of students with low MSE (0 through 3) ( χ 2  = 7.979, df = 1, p  < .01). The remaining career activities did not differ significantly based on students’ MSE. The results are summarized in Table  6 .

These results show that most of the preferred career activities had no correlation at all with MSE scores. However, reading, study, analysis, and investigation are the hallmarks of a mathematics-, science-, or technology-based activity. Therefore, it is reasonable that students who are confident and comfortable with mathematics would also enjoy reading, study, analysis, and investigation.

In order to explore whether there is a correlation between MSE and student’s career interests, a chi-square analysis was conducted. The chi-square analysis revealed that only one career interest differed significantly based on students’ MSE score. This career interest was technical and scientific skills. This career interest was listed in the top 2 favorites for career activities by 43.8% of students with high MSE score (between 4 and 5) compared to 36.0% of students with low MSE score (0 through 3) ( χ 2  = 6.558, df = 1, p  = .01). The remaining career interests did not differ significantly based on students’ MSE scores. As with the results for career activities, these results show that most of the career interests were not significantly correlated with MSE and all of the career interests were rated in the top 2 favorites by less than half of the students. It is reasonable that students who are confident and comfortable with mathematics would also be interested in careers involving technical and scientific skills. The results are summarized in Table  7 .

The correlation between grade level and students’ career interests and preferred career activities

The fourth research question (RQ4) addressed whether grade level was associated with student preferences for career interests and activities. There were statistically significant differences by grade regarding some of the career interests, thereby satisfying the first part of the fourth research question. More grade 7 than grade 9 students listed manual and mechanical skills in their top 2 favorites (36.5 vs 29.4%, χ 2  = 6.84, df = 1, p  < .01), as well as creative skills and expression (45.4 vs 37.0%, χ 2  = 8.73, df = 1, p  < .01). More grade 9 than grade 7 students ranked “working with people” in their top 2 favorites (52.8 vs 46.8%, χ 2  = 4.21, df = 1, p  < .05). These results are summarized in Table  8 .

More grade 7 than grade 9 students listed practical, productive, and concrete activities in their top 2 favorites (42.1 vs 34.7%; χ 2  = 6.9, df = 1, p  < .01). More grade 9 than grade 7 students rated helping others and being concerned for their welfare in their top 2 favorite career activities (34.9 vs 28.6%; χ 2  = 5.4, df = 1, p  < .05) as well as having things organized into routines and having order (39.4 vs 29.4%; χ 2  = 13.2, df = 1, p < .01). There were no statistically significant differences by grade level for the other career activities studied.

This trend is similar to that emerging in the analysis of career interests. In general, students in the higher grade focused more on activities involving helping others and being less attracted to careers that involved practical applications or routines. The results are summarized in Table  9 .

The correlations between students’ STEM career knowledge, mathematics self-efficacy, and grade level on their likelihood to choose a STEM career

The fifth research question (RQ5) focused on how several aspects might relate to students’ likelihood of choosing a STEM career. These areas included grade level, MSE, knowledge of STEM careers, and preferences for various career interests and activities.

First, a logistic regression was conducted to determine whether or not grade level, STEM knowledge, and MSE score were associated with students’ likelihood to pursue a STEM career. The hypothesized regression model was likelihood of choosing a STEM career (ODDS) =  f (grade level, STEM knowledge score, MSE score). A test of the full regression model against an intercept-only model was statistically significant ( χ 2  = 76.85, df = 3, p  < .01). The regression was strong with a McFadden’s R 2  = .85.

The regression analysis correctly classified 70.6% of all cases and 95.3% of those who were likely to choose a STEM career. The regression revealed that students with stronger SCK scores were marginally more likely to pursue a STEM career than were students with weaker SCK scores (odds ratio = 1.04, probability = .51). However, students with high MSE scores were 1.3 times more likely to pursue a STEM career than were those who had lower MSE scores (probability = .56). Grade level was not a statistically significant predictor of the likelihood of pursuing a STEM career.

These results showed that students’ knowledge of STEM careers and their self-efficacy in mathematics were statistically significant factors in the likelihood that they would pursue a STEM career, while STEM career knowledge was a modest contributor. Also, students in grade 9 were not more likely to pursue a STEM career than were students in Grade 7. However, research has shown that occupational intentions change dramatically between 9th and 11th grades and the relationship between STEM intention and motivation is very time-sensitive (Mangu et al. 2015 , p.55). The results are summarized in Table  10 .

These regression results reveal that individual student characteristics, MSE, and SCK are better predictors of the likelihood to pursue STEM careers than student grade level. Individual strengths and weaknesses, as well as students’ knowledge and competency, are better indicators of future career paths than grade level.

The correlation between students’ career interests and their likelihood to pursue a STEM career

A second logistic regression was conducted to explore whether or not students’ preferred career interests was correlated with their likelihood to pursue a STEM career. Six career interests were explored in the analysis. The hypothesized regression model was likelihood of choosing a STEM career (ODDS) =  f (manual and mechanical skills; technical and scientific skills; creative skills and expression; working with people; leading, persuading, and directing others; routines and adhering to standards). A test of the full regression model against an intercept-only model was statistically significant ( χ 2  = 119.94, df = 6, p  < .01). The regression was reasonably strong with a McFadden’s R 2  = .73. The regression analysis correctly classified 72% of all cases and 96.6% of those who were likely to choose a STEM career.

The regression revealed that students who rated technical and scientific skills in their top 2 favorite career interests were 5.4 times more likely to pursue a STEM career (probability = .84). Students who rated working with people in their top 2 favorites were 1.5 times more likely to pursue a STEM career (probability = .61). Students who rated creative and expressive skills in their top 2 favorite career interests were less likely to pursue a STEM career than those who rated creative and expressive skills highly. Their odds of pursuing a STEM career were only .70 of those who did not rate creativity and expressiveness among their favorite career interests. Their probability of pursuing a STEM career was .41. The remaining career interests were not statistically significant predictors of the likelihood of pursuing a STEM career (manual or mechanical skills; leading, persuading, or directing others; routines and adhering to standards). These results provide evidence for the fifth research question in that three out of the six career interests measured did have a statistically significant correlation with the likelihood that a student would consider pursuing a STEM career. The results are summarized in Table  11 .

These results indicate that student preference for technical and scientific skills and careers involving working with people enhance the likelihood of pursuing a STEM career, while students who prefer careers involving creative skills and expression are less likely to do so. While a focus group could better explore the students’ preferences for creativity and creative careers, this level of detail is not possible in large sample survey-based research and is outside of the scope of this study. Other career interests that focus on mechanical, manual, or routine activities, or those involving leadership, do not predict the likelihood of students pursuing a STEM career and are not significantly correlated with STEM career choice.

A third logistic regression analysis was conducted to determine whether students’ career activity preferences were correlated whether or not they were likely to pursue a STEM career. Six career activities were explored in the analysis. The hypothesized regression model was likelihood of choosing a STEM career (ODDS) = f (practical, productive, concrete activities; reading, study, analysis, and investigation; artistic, unusual, and creative activities; taking responsibility, providing leadership, and convincing; and helping others and being concerned for their welfare). A test of the full regression model against an intercept-only model was statistically significant ( χ 2  = 32.883, df = 6, p  < .01). The regression was reasonably strong with a McFadden’s R 2  = .78. The regression analysis correctly classified 72% of all cases, and 100% of those who were likely to choose a STEM career.

The regression revealed that students who preferred career activities involving reading, study, analysis, and investigation were 1.8 times more likely to pursue a STEM career (probability = .65) than those who did not prefer such activities. Students’ rating career activities involving routines and having an order were 1.5 times more likely (probability = .60) to pursue a STEM career than those who did not prefer such activities, while students with preferences for practical, productive, and concrete career activities were 1.5 times more likely to pursue a STEM career (probability = .60) compared to those who did not prefer such activities. The remaining career activities were not statistically significant predictors of the likelihood to pursue a STEM career (artistic, unusual, and creative activities; taking responsibility, providing leadership, and convincing others; helping others and being concerned for their welfare). These results revealed three out of the six career activities measured did have a statistically significant correlation with the likelihood that a student would consider pursuing a STEM career. The results are summarized in Table  12 .

These results stand in contrast to those for students’ career interests and the likelihood of pursuing a STEM career. Unlike the career interest analysis, students seeking routine career activities are more likely to pursue a STEM career. Also, students who ranked career interests involving helping others were more likely to pursue STEM careers, but this analysis showed that student preference for career activities involving helping others and being concerned for their welfare was not a statistically significant indicator of their likelihood to pursue a STEM career. Further, these results differ somewhat in terms of students’ preferences for practical activities. While career interests involving manual or mechanical skills were not statistical indicators of the likelihood of pursuing a STEM career, career activities involving practical, productive, and concrete activities were statistically significant. The career activity involving reading, study, analysis, and investigation was also statistically linked to students’ likelihood to pursue a STEM career, which seems reasonable given that such activities are at the heart of many STEM careers.

Youth vary widely in their career knowledge, interest, and intentions. Factors investigated in the present study examined STEM career knowledge, MSE, career activities, career interests, and the likelihood of students to pursue a STEM career.

Knowledge and self-efficacy

Results of the present study align with recent findings by Compeau et al. ( 2016 ), Nugent et al. ( 2015 ), and Zhang and Barnett ( 2015 ) show that self-efficacy along with knowledge of STEM careers are significant factors in whether or not adolescents pursue STEM careers. Findings also indicated that career knowledge is limited among middle school students and students seem to be unaware of their limited knowledge regarding STEM preparation. While approximately 70% of students reported that mathematics was an important requirement for a career in mechanical engineering, computer hardware design, and pharmacy, 50% or less were aware that it was also important in careers for ophthalmology, land surveyor, nutrition, and oral hygienist.

The issue of self-efficacy takes on particular significance as students progress through high school. Previous research by Murphy and Beggs ( 2005 ), Heilbronner ( 2009 ), and Mangu et al. ( 2015 ) have noted how young women have a lower self-efficacy in STEM during high school years. Previous research has also shown that interest in STEM and motivation to pursue STEM activities tends to wane over time for all high school students. The results of the current study agree with earlier findings that lower levels of MSE exist; we found approximately 34% of participants had low MSE scale totals. These findings raise concerns about the combined effects of students’ low MSE and their declining interest in STEM from early through to later grades and on the numbers of graduating high school students who will be inclined to choose a STEM career.

Results of the current study demonstrated that students in grades 7 and 9 had a broad range of favorite career activities with the majority (approximately 46%) stating that their strongest preference was for artistic and creative types of activities. Also, all of the possible activities were selected by at least one third of the group. Interestingly, approximately 50% of participants selected their career interest as being “working with people,” but relative to career activities, only one third of participants selected “helping people.” However, this is not surprising given that one can have an interest but may not want to have a career working in that activity. For example, one may be interested in art, but have no interest, or lack sufficient talent, to pursue a career in the field (Holland 1973 ). Also, middle school students may not be able to discriminate between the nuances between career activities and interests in the way that older students and young adults would. Although a focus group study may be able to further elucidate this issue, this is beyond the scope of the current study.

Working with others and participating in creative types of activities are important findings that relate to current issues in education in Canada. A recent study (Ayar and Yalvac 2016 ) found that many STEM careers are team-based, creative, and require technical, scientific, and problem solving skills. However, in Canada, many post-secondary programs continue to focus more on memorizing and replicating science content knowledge. Further study of this possible implication would be worthwhile.

While approximately 70% of participants stated they were likely to choose a STEM career, 30% were less likely to do so. Not all students have the financial means to pursue a career interest. In addition, career interest and motivation are highly time sensitive (Mangu et al. 2015 , p.55). Considering findings from studies such as Ayar and Yalvac ( 2016 ), as well as what we know about the decline in interest in STEM careers as students mature, these results suggest that there is room for increasing awareness, STEM career interest, and providing for better knowledge acquisition in the area of STEM careers. As well, our data suggests that alternative ways of teaching and evaluating STEM courses should be considered. Perhaps a greater emphasis on authentic means of teaching and evaluating STEM content that involves collaboration, problem solving, and application of STEM knowledge might serve to engage learners in more meaningful ways, thereby enabling continued motivation and interest in STEM careers as students progress through secondary and post-secondary education. Does a higher MSE lead students to consider pursuing STEM careers and lead them to becoming more informed about the career requirements or do students who have higher knowledge of STEM careers become more competent in mathematics? Are these factors simply correlational and reflect students who are high in both measures or low in both measures? While these questions cannot be answered in this research, it is interesting to note that MSE may play a role, or be a leading indicator, for STEM career knowledge.

Influence of mathematics self-efficacy on career knowledge, interest and activities

Our results indicate that while there is a relationship between career knowledge and MSE, we did not find a relationship among career interests or activities with MSE. The assumption that having a positive sense of mathematics skill would correlate with STEM career interests and activities was not supported. Follow-up research involving interviews with participants about their understanding of career interests, activities, and MSE, would provide more an in-depth understanding. Based on findings by Simpkins et al. ( 2006 ) it was expected that there would be a relationship among interests, activities and MSE as their findings indicated that in junior high beliefs about competency and interests begin to solidify. Further research may help to uncover reasons for not seeing such a correlation in this analysis.

Influence of grade level on STEM career knowledge, interest, and activities

Results indicate that there were significant differences between grade 7 and grade 9 students in the present study relative to STEM career knowledge. Overall, students in grade 9 were more knowledgeable than grade 7 students about STEM careers. The differences formed an interesting and consistent pattern that more grade 7 students expressed interest in manual and mechanical skills than grade 9 students who tended to have more interest in working with people. Further, more grade 7 students expressed interests in practical and concrete types of activities while more grade 9 students expressed interests in helping people and being concerned for their welfare. Reasons for this shift are not clearly understood. As noted by Lent ( 2005 ), career interest, choice, and personal goals form a complex chain involving performance, self-efficacy, and outcome expectations. As well, socio-cultural factors also need to be considered along with opportunity for exposure (Fouad and Smith 1996 ; Kuncel et al. 2005 ; Lent et al. 1994 ). As with the relationship among self-efficacy, knowledge, interests, and activities, in-depth research involving student interviews may result in greater understanding of the reasons for these shifts and their impact on later careers.

Factors influencing positive statements involving the likelihood of choosing a STEM career

Regression analyses revealed that participants with stronger STEM career knowledge were slightly more likely to pursue a STEM career and that students with higher MSE scores were also slightly more likely to choose a STEM career. Also, grade level was not a differentiating factor, which was anticipated given the small distance between the experiences of grade 7 versus grade 9 students. As noted in many previous studies (Lent et al. 1994 ; Kuncel et al. 2005 ), knowledge of STEM careers and self-efficacy in mathematics are statistically significant factors in the likelihood that participants will pursue STEM careers.

Interest in technical and scientific skills is a strong predictor of the likelihood of pursuing a STEM career with those who indicated a preference for technical and scientific skills being 5.4 times more likely to indicate the likelihood of choosing a STEM career compared to those who rated working with people as their stronger interest. Indeed, preferences for practical, productive, and concrete activities also indicated a stronger likelihood of pursuing STEM careers than those who do not prefer such activities. Implications of these findings point to improving methods for providing information on the skills and nature of the work in STEM careers particularly in fields such as engineering and technology (which have an important focus on team work, problem solving, and creativity) as well as on technical and scientific skills.

Overall, results of the present study show that career knowledge is limited among middle school students and that they have a declining interest in STEM and have low MSE scores. Students are interested in careers that involve a wide variety of activities but do not appear to relate these activities to STEM careers. Our results point to the importance of finding and expanding on ways to increase authentic learning opportunities in secondary school in Atlantic Canada such that students are better able to participate in collaboration, problem solving, and the application of scientific knowledge in their classes. Such learning opportunities would ensure that students have access to more information on the actual nature of work in the STEM field and what is required to pursue these careers. This strategy would also serve as a motivator to those who are not aware that STEM careers involve people skills, creativity, and problem solving.

Abbreviations

Confirmatory factor analysis

• Mathematics self-efficacy

Science, technology, engineering, and mathematics

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Funding was provided to author by a grant from the Natural Sciences and Engineering Research Council of Canada. We are grateful to the individuals who helped our team obtain parental consent forms and parents for providing consent for the children to participate in this study.

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The second author conceptualized the broad goals of the study, and all four authors were part of a research team that designed all the study components and executed the research. The first author was primarily responsible for designing the methodology and quantitative data analysis, while the fourth author assisted with the data analysis. The second and third authors were primarily responsible for conducting the literature review, developing the theoretical underpinnings of the research, and interpreting the results of the analysis from a theoretical perspective. All authors read and approved the final manuscript.

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Blotnicky, K.A., Franz-Odendaal, T., French, F. et al. A study of the correlation between STEM career knowledge, mathematics self-efficacy, career interests, and career activities on the likelihood of pursuing a STEM career among middle school students. IJ STEM Ed 5 , 22 (2018). https://doi.org/10.1186/s40594-018-0118-3

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Quantitative STEM: Experimental Methods and Applications

J M LeBeau 1 , S D Findlay 2 , L J Allen 3 and S Stemmer 4

Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series , Volume 371 , Electron Microscopy and Analysis Group Conference 2011 (EMAG 2011) 6–9 September 2011, Birmingham, UK Citation J M LeBeau et al 2012 J. Phys.: Conf. Ser. 371 012053 DOI 10.1088/1742-6596/371/1/012053

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1 Department of Materials Science and Engineering, North Carolina State University, Raleigh, NC 27606, USA

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4 Materials Department, University of California Santa Barbara, Santa Barbara, CA 93106, USA

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High-angle annular dark-field (HAADF) imaging in scanning transmission electron microscopy (STEM) is highly sensitive to both the atomic number and the Debye-Waller factor of the atom columns. We will discuss the experimental requirements for a quantitative understanding of STEM image contrast, in particular the determination of the precise specimen thickness. We show that near perfect agreement can be achieved between theory and experiment and demonstrate that quantitative STEM allows for column-by-column counting of all the atoms in an arbitrarily shaped specimen.

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