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Understanding and improving undergraduate science education is a national imperative for both a science-literate citizenry and a diverse technical workforce. The President's goal is “to improve the quality of science, technology, engineering, and math (STEM) education at all levels to help increase the number of well-prepared graduates with STEM degrees by one-third over the next 10 years, resulting in an additional one million graduates with degrees in STEM subjects” (http://goals.performance.gov/goals_2013). The emphasis is on quality education to prepare students to innovate and adapt to a fluid scientific world of work. And, the value of an effective science education extends well beyond the traditional definition of the science and engineering workforce (McKinsey & Company, 2009; Auguste, Cota, Jayaram, & Laboissière, 2010; Carnevale, Strohl, & Melton, 2011; Rothwell, 2013). Students are increasingly pursuing certificate programs in community colleges to access good jobs that require scientific understanding and skills (Carnevale, Jaysundera, & Hanson, 2012). To meet workforce needs, we must find better ways to engage and retain diverse groups in undergraduate science learning, currently a challenge (National Research Council, 2011).

There is not a silver bullet solution to the undergraduate science education dilemma where less than 50% of all students who start college intending to major in a STEM field complete a STEM degree within 5 years (National Research Council, 2011). The President's Council of Advisors on Science and Technology (PCAST) conclude, “Retaining more students in STEM majors is the lowest-cost, fastest policy option to providing the STEM professionals that the nation needs for economic and societal well-being” (2012, p. i). Improving instruction in the undergraduate years is a best bet for increasing retention. The PCAST report recommends widespread implementation of evidence-based teaching practices.

Contributions of Discipline-Based Education Research

  1. Top of page
  2. Contributions of Discipline-Based Education Research
  3. Reflections on the State of the Field
  4. References

Concurrent with the PCAST report, the National Research Council released the first synthesis and analysis of undergraduate learning and understanding across science and engineering fields (Singer, Nielsen, & Schweingruber, 2012). This Discipline-Based Education Research (DBER) report from the National Research Council offers compelling evidence that we now know enough about how our students learn and about effective instructional strategies to significantly enhance the undergraduate learning experience; yet the research is still in the early stages with many gaps to be addressed. The report also underscores that evidence is necessary but not sufficient to change undergraduate STEM education. We have yet to see widespread implementation of evidence-based practices and significant research on the effectiveness of different theories of change and theories of action are needed.

This Special Issue of JRST, on Discipline-Center Postsecondary Science Education Research, reflects conclusions and recommendations in the DBER report and makes a substantial contribution to advancing the field. Research on undergraduate science learning is currently a loose affiliation of related fields. The common feature is the focus on undergraduate teaching and learning within a discipline, using a range of methods with deep grounding in the discipline's priorities, worldview, knowledge, and practices. The research has developed within physics, chemistry, biology, geology, and astronomy, often conducted by faculty within the disciplinary departments. Publishing venues tend to be discipline specific, while JRST offers an opportunity for cross-fertilization of ideas amongst the disciplines. Each of the disciplinary fields has emphasized different areas of research and collectively there is much to be learned from a comparative and integrated approach. A second contribution of this issue to the field is that the contributions so clearly advance the research agenda and, in some cases, explore areas identified as gaps in the report. Using the research synthesis of the report as a scaffold, this commentary links approaches and findings in this issue to illustrate the exciting, forward momentum of research on undergraduate science learning and instruction.

In brief, the report identifies several areas where there is a strong evidentiary base: conceptual understanding and, to a lesser extent, conceptual change; problem solving; the use of representation; and effective instructional practices. Emerging areas of research at the undergraduate level include metacognition, transfer, and the affective domain, including attitudes, beliefs, and motivation. To be clear, the research in related areas including K-12 education and cognitive science provides a rich body of evidence in some of these emerging areas, especially metacognition. The work has not been as fully developed in DBER.

In addition, there are areas where there are significant gaps. Studies of similarities and differences among different groups of students would be particularly useful in making science education broad and inclusive. Only a limited number of studies at the undergraduate level disaggregate data. For example, Student-Centered, Active Learning Environment for Undergraduate Programs (SCALE-UP) learning environments help close the gender gap (Gaffney et al., 2008). Longitudinal studies would enhance our understanding of how expertise develops over the undergraduate years. Additional basic research on learning in the disciplines during the undergraduate years is needed, as are interdisciplinary studies of crosscutting concepts and cognitive processes. And, if the research findings on practices that increase student success are to be effectively implemented, the research agenda must include work on translating research findings into practice.

Reflections on the State of the Field

  1. Top of page
  2. Contributions of Discipline-Based Education Research
  3. Reflections on the State of the Field
  4. References

Conceptual Understanding and Conceptual Change

Ding, Chabay, and Sherwood (Article #5) developed a 33-item concept inventory that assesses student understanding of core energy concepts. Valid and reliable concept inventories have been developed across the science disciplines and provide instructors with simple, affective tools to identify student misconceptions and determine if conceptual change occurred during a course. This concept inventory illustrates a way to further work on interdisciplinary learning as energy is essential across all science disciplines and all to often the chemistry student fails to see any connection between the energy concepts being introduced in the chemistry course and the energy concepts introduced in a prior biology course. As the authors remind us, energy is a crosscutting concept highlighted in the Framework for K-12 Science Education, which guided the development of the Next Generation Science Standards (NRC, 2012). The energy concept inventory illustrates the potential for studies focused on undergraduates to be of use in pre-college learning environments and, likewise, for pre-college research to inform undergraduate science education research.

While concept inventories continue to be developed as effective means to investigate students' conceptual understanding, progress on conceptual change has been slower, falling into the category of much needed basic research. Here Dega, Kriek, and Mogese's (Article #3) careful work on conceptual change in electricity and magnetism identified an effective intervention, cognitive perturbation through interactive simulations. This work, conducted in Ethiopia, adds to a number of areas identified in the DBER report as needing research. The work is theory driven, illustrates the power of collaboration across multiple disciplines, and integrates both physics and cognitive psychology expertise to solve a complex problem. It delves deeply into not only the cause of a misconception but deliberate strategies to alter it. The DBER report notes that the data on the effectiveness of simulations are promising and this work adds to that evidence base.

Use of Representations

Students have particular difficulty with concepts that are at either very large or very small temporal or spatial scales. This is a challenge for students learning about small molecules. Cooper, Corley, and Underwood's work (Article #4) provides a compelling example of conceptual understanding and change research that includes students' representations of molecules. Prior work by Cooper's team established student's difficulties in relating structure to properties ranging from drawing structures to making predictions about properties based on structure. Through an interview protocol they documented that students could achieve above average scores on an American Chemical Society exam and yet still not grasp fundamental chemistry concepts. By asking students to make drawings in responding to questions, the team unpacked many challenges students face, including misusing or overusing heuristics. The shorthand heuristics can allow students to reason a correct answer without understanding. While students struggle with representation, this study identified multiple sticking points for students; multiple ideas, skills, and heuristics need to be effectively integrated to move a student towards a correct understanding. Cooper's work moves the field towards a more nuanced understanding of students' conceptual challenges with structure–property relationships, essential for developing effective interventions.

Dauer, Momsen, Speth, Makohon-Moore, and Long (Article #1) also use representations to understand conceptual change, specifically iterative models that link process at the molecular level with population level change. The authors make the case for the use of models in formative and summative assessment, including identifying which concepts are especially challenging. As with Ding, Chabay, and Sherwood's research, there are important links with pre-college learning that cut both ways. The Next Generation Science Standards include modeling as one of the science and engineering practices. Being ready for students with that type of pre-college learning experience when they arrive in introductory college courses can be enhanced by Long and colleague's research. Further, understanding how to effectively develop pre-service teachers' modeling skill is a priority.

Problem Solving

Both Talanquer (Article #6) and Cooper's research group investigated the role of heuristics in student problem solving strategies in chemistry, specifically structure and property relationships. The two groups utilized interview protocols to identify student reasoning strategies for structure–property problems. Talanquer identified a pattern of reasoning that may be common to college students, especially under stressful conditions. In both studies the default to one-reason decision making allows students to get to an answer more quickly. But without a more developed understanding, students can both oversimplify and overgeneralize, arriving at an incorrect conclusion. The lesson learned is not that heuristics should be eliminated, but that student learning should be scaffolded so they apply heuristics in the correct context. The basic research on student reasoning in solving structure–property problems supports development of appropriate guides and prompts which have been shown to help a student move towards expertise.

Instructional strategies

Much of the research in this issue of JRST builds the foundational knowledge to inform improved instruction. Lopez, Nandagopal, Shavelson, Szu, and Penn (Article #2), however, investigate students' study strategies. The most common strategies used are review strategies that do not correspond with course success. The implications for instructional practice include creating learning environments that give students the opportunity to participate in metacognitive activities and peer learning to enhance their understanding. This study also makes steps towards examining differences among different groups, a gap noted in the DBER study. Although different ethnic groups had similar study patterns, the authors suggest that both the nature of the commuter campus where the study was conducted and using ethnicity as a proxy for cultural and ethnic experiences should be considered before generalizing the findings.

Conclusion

Collectively, the six research articles in this special issue illustrate a range of methodologies used in research on how undergraduate students learn STEM, build on prior findings and theoretical frames within the field, as well as drawing upon work in K-12 learning and cognitive science, and increase our understanding in both established and emerging areas of undergraduate science education research. Further research on change in higher education science instructional practices will be necessary for these findings to inform practice. As important as widely implementing effective practice is, a sustained focus on advancing research on understanding and improving undergraduate science learning is also key to providing all students with high quality science learning and learning environments, developing the workforce in science and science-related fields, and broadening participation in science.

References

  1. Top of page
  2. Contributions of Discipline-Based Education Research
  3. Reflections on the State of the Field
  4. References
  • Auguste, B. G., Cota, A., Jayaram, K., & Laboissière, M. C. A. (2010). Winning by degrees: The strategies of highly productive higher-education institutiona. San Francisco, CA: McKinsey & Company.
  • Carnevale, A. P., Jayasundera, T., & Hanson, A. R. (2012). Five ways that pay along the way to the B.A. Washington, DC: Georgetown University Center on Education and the Workforce.
  • Carnevale, A., Strohl, J., & Melton, M. (2011). What's it worth: The economic value of college majors. Washington, DC: Georgetown University Center on Education and the Workforce.
  • Gaffney, J. D. H., Richards, E., Kustusch, M. B., Ding, L., & Beichner, R. (2008). Scaling up educational reform. Journal of College Science Teaching, 37(5), 4853.
  • McKinsey & Company. (2009). Changing the fortunes of America's workforce: A human capital challenge. San Francisco, CA: McKinsey Global Institute.
  • National Research Council. (2011). Expanding underrepresented minority participation: America's science and technology talent at the crossroads. Washington, DC: National Academies Press.
  • National Research Council. (2012). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. Washington, DC.: National Academies Press.
  • President's Council of Advisors on Science and Technology. (2012). Engage to excel. Washington, DC: White House.
  • Rothwell, J. (2013). The hidden STEM economy. Washington, DC: Brookings.
  • Singer, S. R., Nielsen, N. R., & Schweingruber, H. A. (2012). Discipline-based education research. Washington, DC: National Academies Press.