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From Psychology Laboratory to Student Development: Untangling Momentary Engagement from Longer-Term Engagement in Bioscience Education

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Chapter
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Reform movements in undergraduate STEM education call for the implementation of active learning strategies that have received much attention in national reports. Active learning encompasses a range of instructional practices that engage students in learning through activities and/or discussion, as opposed to passively listening to an expert. These practices benefit STEM undergraduates by enhancing their conceptual understandings, their focus on instruction, their critical thinking skills, and their persistence in STEM fields. This chapter defines active learning, describes a conceptualization of active learning practices along a continuum of how challenging they are for instructors to adopt, and provides overviews of common active learning approaches.
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As the evidence for the value of active learning in STEM classes grows, questions arise about how to implement such approaches to maximize their effectiveness. Definitions of active learning can lead us to believe that if students are doing content-related work in class rather than listening to lecture, their learning will naturally be improved. But research has shown that this is not necessarily the case. Successful active learning strategies in face-to-face classes depend on a multitude of factors, including question and activity design, faculty prompts, student incentives for participation, and group dynamics. In this chapter I discuss what research suggests is a key underlying reason that these factors impact the results of active learning approaches—their effect on the level of students’ cognitive engagement. In this chapter, I discuss the ICAP (interactive, constructive, active, passive) framework for student engagement and how it manifests in various active learning formats. This framework explains how certain student behaviors during active learning evoke deeper processing of ideas and, thus, lead to better student learning.
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In recent years college science instructors have been buffeted by four interrelated but essentially independent challenges with potentially strong implications for classroom teaching. The first of these challenges is the widespread and deeply felt dissatisfaction with the status quo registered by many science students and extensively documented by Seymour and Hewitt (Seymour E, Hewitt N, Talking about leaving: why undergraduates leave the sciences. Westview Press, Boulder, 1997). The second and third are the epistemological (Kuhn T, The structure of scientific revolutions. University of Chicago Press, Chicago, 1962) and cognitive (Atkinson R, Shiffrin R, Human memory: a proposed system and its control processes. In Spence K, Spence J (eds) The psychology of learning and motivation. Academic, New York, 1968) revolutions upending the cherished notion of the objective observer in science. And the fourth is the growing recognition of the importance of collaborative work in the natural sciences (Vygotsky L, Mind in society: the development of higher psychological processes. Harvard University Press, Cambridge, MA, 1978) and in disciplines outside of science. This chapter offers a framework for thinking about and constructing active learning environments, providing a rational, evidence-based, and discipline-centered response to these challenges.
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The literature on active learning is full of success stories, but how many instructors have tried and failed to implement new teaching strategies? This chapter discusses the four main factors that impede successful adoption of active learning: student resistance, instructor reluctance, administrative roadblocks, and physical settings. Some of these barriers, such as institutional policies and underlying instructor beliefs about the role of teachers and students, are difficult to overcome. Most of the barriers can be eliminated through faculty development and course design that includes teaching students metacognition and the skills needed to be successful in self-directed learning environments. The chapter ends with suggestions for facilitating implementation of active learning.
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Evidence within the science, technology, engineering, and mathematics (STEM) disciplines demonstrates that engagement in the learning process is pivotal for students’ development of conceptual understanding in their respective field of study. Achieving such engagement depends largely on the extent to which faculty incorporate active-learning strategies (ALSs) into their curricula in a purposeful manner. Specifically, ALSs should be aligned to explicit student learning objectives and forms of assessment in order to assist students in acquiring deep understanding of the content. In this chapter, we first define active learning and provide several examples of common ALSs. Subsequently, we discuss the relationship between active learning and students’ development of conceptual understanding in the biological sciences, with particular attention given to factors that have the potential to mediate that relationship. We conclude by offering recommendations for how faculty might assess conceptual understanding in their own classrooms as well as the efficacy of ALSs more broadly.
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Improving student performance on exams is a key issue that many psychology instructors face in their classrooms. One potentially easy to deploy option for improving student performance is an exam wrapper. In this article, I detail two studies that compared exam wrappers to a control condition (a previous semester in Study 1 and a within course control condition in Study 2). Both studies found notable improvements in student exam performance above what is typically seen in the course. This suggests that the exam wrapper is an easy-to-employ tool for your students to use to improve their test preparation and performance.
Article
Cognitive science research on learning and instruction is often not directly connected to discipline-based research. In an effort to narrow this gap, this essay integrates research from both fields on five learning and instruction strategies: active retrieval, distributed (spaced) learning, dual coding, concrete examples, and feedback and assessment. These strategies can significantly enhance the effectiveness of science instruction, but they typically do not find their way into the undergraduate classroom. The implementation of these strategies is illustrated through an undergraduate science course for nonmajors called Science in Our Lives. This course provides students with opportunities to use scientific information to solve real-world problems and view science as part of everyday life.
Article
Blended courses which mix in-person instruction with online platforms are increasingly common in secondary education. These platforms record a rich amount of data on students' study habits and social interactions. Prior research has shown that these metrics are correlated with students' performance in face to face classes. However, predictive models for blended courses are still limited and have not yet succeeded at early prediction or cross-class predictions even for repeated offerings of the same course. In this work, we use data from two offerings of two different undergraduate courses to train and evaluate predictive models of student performance based upon persistent student characteristics including study habits and social interactions. We analyze the performance of these models on the same offering, on different offerings of the same course, and across courses to see how well they generalize. We also evaluate the models on different segments of the courses to determine how early reliable predictions can be made. This work tells us in part how much data is required to make robust predictions and how cross-class data may be used, or not, to boost model performance. The results of this study will help us better understand how similar the study habits, social activities, and the teamwork styles are across semesters for students in each performance category. These trained models also provide an avenue to improve our existing support platforms to better support struggling students early in the semester with the goal of providing timely intervention.
Article
The Cambridge Handbook of Cognition and Education - edited by John Dunlosky February 2019
Chapter
Gamification is often utilized to enhance the motivation to use digital learning tools. Usually, the effect of gamification alone is not sufficient to achieve sustainable self-directed occupation of students with digital learning tools. This statement is also confirmed by the authors' experiences from previous uses of quiz apps to impart factual knowledge. The presented study describes the use of gamification in a university course in Urban Water Management in a twofold approach. The first approach of gamification is a gamified quiz app, which offers matches as well as ranking lists and competitions. The second approach is the gamified integration of the quiz app into the didactic context. The didactic context is characterized by the voluntary use of the quiz app and meaningful incentives , such as substitution of preliminary assessment tests. Compared to previous experiences, students showed a high level of engagement. Research instruments are the usage data of the quiz app and data collection at four points in time with the help of standardized measurement instruments (QCM, EGameFlow, and expectation-value model). The results include outstanding engagement of students indicated by an average of 2,223 questions per student answered during the semester, a high degree of confidence in mastering learning tasks among students , and a comparatively high level of knowledge improvement and social interaction reported by students. Overall, the study demonstrates the huge impact of deep gamification by integrating gamification into the didactic context and encourages further systematic research of deep gamification of didactic contexts.
Article
Studies completed with undergraduate populations have shown that attendance positively correlates with academic performance. A marked decline in classroom attendance within medical school has recently been noticed with the availability of video capture of lectures and other online material. This study compares these in the era of online material. It took place during the second-year Gastrointestinal and Renal Systems module. Attendance was mandatory at team-based learning and case-based learning sessions on new material and voluntary at lectures (29 sessions) and case-based learning on material previously covered (9 sessions). Attendance was recorded prospectively. All lectures were recorded, and all related files were available to students online. Performance was based on a 118 multiple-choice question final examination. Students voluntarily completed the Motivated Strategies for Learning Questionnaire (MSLQ). The study group consisted of 78 students (68% of 114 total) of whom 48 completed the MSLQ. Mean attendance was 24%, with 33% of students attending none of the nonmandatory sessions. The median score on the final exam for participants was 86.0 (range: 28.8). High levels of self-efficacy and the ability to self-regulate effort were predictive of low attendance. Attendance was positively predicted by an orientation toward peer learning and help seeking. There was no correlation between the percentage of classes attended and performance on the final exam. We conclude that different facets of self-regulated learning predict attendance, with highly confident students being the least likely to attend, and that attendance at in-class sessions is no longer a good marker for performance.
Article
We investigate a model based on Self-Determination Theory (SDT) to predict academic achievement and dropout intentions among biology students in higher education in Norway. Students (n=754) from a representative national sample participated in this cross-sectional study. The results align with our hypotheses and SDT assumptions. The model explains a substantial amount of the variance in academic achievement and dropout intentions. Specifically, autonomous motivation and perceived competence positively predict academic achievement and negatively predict dropout intentions. Controlled motivation is unrelated to academic achievement and is a positive predictor of dropout intentions. Furthermore, significant indirect effects show that need-supportive teachers and students’ intrinsic aspirations positively predict academic achievement and negatively predict drop- out intentions, via autonomous motivation and perceived competence. We recommend teachers to support students’ need for autonomy, competence and relatedness, by providing choice and volition to facilitate autonomous motivation, and give students effectance-relevant feedback and optimal challenges to increase perceived competence.
Article
The international business education literature suggests that a global mindset can be acquired and benefit students to embrace new ideas and improve their critical thinking. Using a sample of 1,448 undergraduate students in Corporate Finance, International Finance, and Business Law subjects during 2013–2015, our results indicate that students with better academic performance in the subject Global Economic Environment achieve a better learning outcome in advanced functional business subjects. However, students with a better global mindset do not benefit as much from the Classroom Response Systems (CRSs) as the weaker students do.
Article
Learning science is an emerging interdisciplinary field that offers educators key insights about what happens in the brain when learning occurs. In addition to explanations about the learning process, which includes memory and involves different parts of the brain, learning science offers effective strategies to inform the planning and implementation of activities and programs in continuing education and continuing professional development. This article provides a brief description of learning, including the three key steps of encoding, consolidation and retrieval. The article also introduces four major learning-science strategies, known as distributed learning, retrieval practice, interleaving, and elaboration, which share the importance of considerable practice. Finally, the article describes how learning science aligns with the general findings from the most recent synthesis of systematic reviews about the effectiveness of continuing medical education.
Article
Science education reform efforts in the Unites States call for a dramatic shift in the way students are expected to engage with scientific concepts, core ideas, and practices in the classroom. This new vision of science learning demands a more complex conceptual understanding of student engagement and research models that capture both the multidimensionality and contextual specificity of student engagement in science. In a unique application of person-oriented analysis of experience sampling data, we employ cluster analysis to identify six distinct momentary engagement profiles representing different combinations of the behavioral, cognitive, and affective dimensions of student engagement in high school science classrooms. Students spend a majority of their classroom time in one of several engagement profiles characterized by high engagement on one dimension, but low levels on the others. Students exhibited low engagement across all three dimensions of engagement in about 22% of our observations. Full engagement, or high levels across all three dimensions, is the least frequent profile, occurring in only 11% of the observations. Students’ momentary engagement profiles are related in meaningful ways to both the learning activity in which students are engaged and the types of choices they are afforded. Laboratory activities provided especially polarized engagement experiences, producing full engagement, universally low engagement, and pleasurable engagement in which students are affectively engaged but are not engaged cognitively or behaviorally. Student choice is generally associated with more optimal engagement profiles and the specific type of choice matters in important ways. Choices about how to frame the learning activity have the most positive effects relative to other types of choices, such as choosing whom to work with or how much time to take. Results are discussed in terms of implications for practice and the utility of the methodological approach for evaluating the complexities of student engagement in science classrooms.
Conference Paper
An exam wrapper is a structured activity that students engage in after their instructor has graded and returned an exam, and is designed to promote self-reflection and improve study practices. This paper describes two studies examining the efficacy and student perceptions of exam wrappers. The studies were conducted at two major Canadian universities, using complementary research designs. We report that neither study produced evidence that exam wrappers have a significant effect on final exam scores or on course drop rates. However, we also find that the use of wrappers was associated with improved rates of test pickup and increased scores on a course evaluation question regarding the fairness of evaluation methods. Given these results, we advise instructors who are considering the use of exam wrappers to review the evidence for other possible interventions that may more effectively serve the same goals.