When they were students, many current science instructors learned through traditional lectures. This mode of passive knowledge transmission has been shown to be less effective for student learning than an approach that involves students in a more active and engaged role in their learning. Without first-hand experiences with active learning, current instructors face challenges as they try to incorporate active learning experiences into their classrooms. In this review, we summarize the field of active learning, including relevant pedagogical philosophy and features of commonly used activities. We end with future considerations that could help disseminate and improve the implementation of active learning in college science classes.
Choi, Y., Jakob, S., and Anderson, W.J. 2017. Active Learning: Developing Self-Directed Learners Through Strong Intellectual Engagement. CourseSource. https://doi.org/10.24918/cs.2017.20
During learning, the brain is hardly dormant. At the molecular level, neurons in the brain produce and degrade more than a hundred different proteins within four hours after learning (1). There is a stark contrast between the dynamic movements of the molecules and signals needed for learning and the traditional classroom, where students sit passively listening to the lecturer.
For many years, educators in the fields of science, technology, engineering, and mathematics (STEM) have been campaigning for a change in teaching methods to reinvigorate the science classroom (2-4). The term active learning has emerged as a key ingredient of recent science education reform, which seeks to equip instructors with new educational tools and improve the way students learn. Over the last few decades, active learning has become a central topic in the educational literature (Figure 1). In 2016, PubMed alone cataloged roughly 265 publications on active learning. This increase in educational research resulted in the expansion of active learning strategies in different fields of education, as well as more rigorous analysis of the effectiveness of active learning techniques on student learning.
In this review, we aim to provide science instructors, who may not be versed in active learning, with a concise introduction to active learning interventions. This introduction will include the definition of active learning as well as its educational context, features, and effectiveness. We also include a list of active learning interventions and web-based resources, and conclude with a brief discussion of future directions in the field. We direct readers who are interested in specific active learning interventions to other recent comprehensive reports (for example, see 2, 5-10).
What is active learning?
There are numerous explanations and definitions of the term "active learning" in the educational literature as well as in non-professional contexts. Each definition differs slightly from others. Arguably one of the best lexical definitions of active learning was suggested by Collins and O'Brien (11):
"[Active learning is] The process of having students engage in some activity that forces them to reflect upon ideas and how they are using those ideas. Requiring students to regularly assess their own degree of understanding and skill at handling concepts or problems in a particular discipline. The attainment of knowledge by participating or contributing. The process of keeping students mentally, and often physically, active in their learning through activities that involve them in gathering information, thinking, and problem solving."
The quote above explicitly demonstrates a key component of active learning - active mental engagement. What is implicit in the quote is that active learning encourages students to own their learning, the second component of active learning (12) (Figure 2).
Two pillars of active learning: self-directed learning and active mental engagement
Instead of being passive learners, students in an active learning setting are prompted to become responsible for their own learning (12-13). Self-directed learning, sometimes also referred to as flexible learning in the literature (14), emphasizes a focus on the students and learning, as opposed to the teacher and teaching. Phrases often used to describe this concept are "teaching more by talking less" (15) and "show, don't teach" (16). To motivate students to follow their own curiosity and take ownership of their learning, some active learning interventions ask students to formulate their own hypotheses, design experiments, and solve open-ended problems (17-20).
In general, descriptions of active learning contain verbs that describe student action, indicating that active learning interventions entail meaningful, hands-on/minds-on activities designed to invite students to think about what they are learning (10,21-22). Active learning requires strong intellectual involvement through higher-order thinking. When the learning objectives require complex cognitive tasks such as application, evaluation, and synthesis of knowledge (23-24) (Figure 3), students benefit from active learning interventions inherently designed to elicit strong intellectual involvement.
It is important to note that these two elements of active learning - self-directed learning and strong intellectual engagement - are independent from each other. For example, an active learning intervention may ask students to simply recall factual knowledge (low on the Bloom's scale). Conversely, critical thinking can also be prompted in a traditional lecture setting (12,25-26). Therefore, when designing active learning interventions, educators should keep in mind that active learning interventions need to promote both student autonomy and deep thinking (12).
How can one elicit active intellectual engagement?
For the last few decades, teachers and educators have been emphasizing the need to better facilitate learning in their students. Over this time, two main concepts have emerged and been refined to form the cornerstones of fostering active intellectual engagement in students.
Encourage students to construct their own knowledge and incorporate new knowledge into an existing framework
The classical way of teaching, often referred to as the empty vessel model or objectivism, sees the instructor standing in front of the class telling the students about a certain topic (27-28). The teacher is simply transferring information, expecting the students to absorb and replicate the knowledge. In contrast, constructivists deny the notion that knowledge can be mechanically transferred to and replicated in a learner (27,29). Instead, constructivists consider learning to be a process in which students construct the knowledge for themselves (29-33). In this model, the teacher becomes a "knowledge facilitator," who aims to create an environment in which constructive learning can happen (Figure 4).
Studies directly comparing traditional versus constructivist teaching found that constructivist teaching leads to an increase in student engagement and greater learning as measured by test scores (35-36). Interestingly, some of history's greatest scientists and teachers already understood the importance of having students construct their own knowledge. For example, Albert Einstein has been quoted as saying "I never teach my pupils; I only attempt to provide the conditions in which they can learn" (http://www.quotationspage.com/quote/40486.html).
A characteristic of constructivist teaching is to compare and contrast new information to pre-exiting knowledge.Learning does not happen in a vacuum. Instead, learners create an internal interpretation of new information based on their prior experiences. One illustration of this idea is a scene from Antoine de Saint Exupéry's The Little Prince, in which a drawing can be interpreted either as a hat or as a boa constrictor digesting an elephant, depending on the interpreter and his/her prior experience. In a recent study that examined the effect of pre-existing background knowledge on learning of vocabulary and comprehension skills in pre-school children, students with existing background knowledge performed better in a given task than those without that knowledge (37). The researchers also showed there are no differences between the two groups when the task was unrelated to particular prior knowledge (37).
As a result of the impact of existing knowledge on learning, the process of true learning often must resolve conflicts between previous understanding and new ideas (a concept referred to as cognitive dissonance) and the subsequent assimilation of new knowledge (38-39). Educators can induce cognitive dissonance by challenging students to critically evaluate their existing knowledge and address misconceptions (40). Furthermore, using real-life questions and scenarios in active learning interventions can create the context to which students can link new concepts. A study using instructor-generated "pseudo peer" diagrams to elicit cognitive dissonance in first year engineering students, found that students using these models were more likely to notice key features and identify misconceptions in their own work (41). Identifying cognitive dissonance can also motivate students to evaluate previous knowledge more critically and be open to potentially changing their existing framework.
Reflect on the progress of one's own learning
Challenging students' prior knowledge and aiming for higher-order thinking through application of the acquired knowledge are part of metacognition, the continuous reflection on the ongoing learning progress. John Flavell, a pioneer of the work in this field, defined metacognition as "one's knowledge concerning one's own cognitive processes and products or anything related to them" (42). In other words, students need to have knowledge of their cognitive abilities (i.e., knowledge about the learners themselves as well as their learning strategies) and the need to be able to monitor their learning process (i.e., ability to plan and predict, evaluate and assess) (43-44). Studies have suggested that high metacognitive skills promote effective structuring and evaluation of one's knowledge, which are necessary for academic and cognitive achievement (43,45-46).
Students benefit most from this metacognitive process only when it is guided. While enrolled in a course, students are constantly exposed to course material through lectures, office hours, assignments, etc. This persistent exposure can evoke a false sense of knowledge. For example, when people are asked to retrieve a memory, they partially rely on a "feeling of knowing" and tend to be overconfident about their recollection (47-49). In a recent study, researchers gave participants an easy test about North American geography with the intent to enhance participants' self-perceived expertise in the subject. These participants were more likely to claim knowledge of nonexistent places (e.g., Cashmere in Oregon) than another group of participants who were given a more difficult test (50). In addition to overestimating what they know, students often confuse factual surface knowledge with deep understanding, a phenomenon sometimes referred to as the illusion of explanatory depth (51-52). This false sense of knowledge is even worse than lack of knowledge since the students do not realize that they are missing crucial details.
Therefore, incorporating frequent assessments of both the lecture material and the students' metacognitive processes as part of the instructional routine can enhance student learning. Other ways of helping students monitor their own learning progress include outlining goals and objectives, providing practice questions for students to test their knowledge, giving writing assignments that prompt students to reflect the lecture material or exams, and using peer review / peer learning (e.g., students teaching each other, small group assignments, etc.) (53-56).
Active learning strategies
Features of active learning interventions
Active learning strategies that are widely used in STEM courses have different formats, but they share some common characteristics (Table 1).
First, all active learning interventions elicit active engagement of all students with the course material. This engagement is especially important in large instructor-led courses in which only a very small number of students could otherwise participate (e.g., by answering the occasional questions posed to the group by the instructor). Activities involving clickers or peer discussions have been shown to be inclusive of a more diverse set of learners and increase student learning as well as overall participation (35,57-58).
Second, active learning interventions often encourage students to explain their knowledge and reasoning to themselves or peers. The positive effect of explanation on learning has been well documented (59). In particular, explanation helps the learner apply newly acquired concepts to novel situations (60-63). A study done in an undergraduate genetics course revealed that peer discussion improves student learning by gains in conceptual understanding, not by simple influence of peers (64).
Third, some of the active learning interventions facilitate two-way communication between students and the instructor. Many in-class active learning interventions provide the medium through which instructors directly learn about their students' level of understanding. Indeed, active learning interventions have a component of assessment (65) in them. This immediate feedback allows instructors to respond and adjust their teaching based on student understanding.
Fourth, active learning interventions often include homework assignments that require higher-order thinking than was practiced in class (23-24), asking students to apply knowledge, analyze data, generate new ideas, etc. These assignments not only compel students to delve deeper into the material, but ideally can also tap into student creativity.
Evidence for effectiveness of active learning
A recent meta-analysis of 225 studies that tested the effect of active learning in undergraduate STEM education showed that active learning resulted in higher exam scores and lower failure rates than traditional lecturing (66). Other studies with randomized control groups and more rigorous experimental regimens strengthen the conclusion that active learning improves learning for all students (67-69).
A study in a physiology course showed that, in a traditional lecture course, students with little science background usually performed worse than students who had a stronger science background. However, after active learning was incorporated into the course, all students showed a benefit. Additionally, the students with little science background performed as well as those who entered with a stronger science background (70). Therefore, active learning can provide more equitable opportunities for less prepared students to learn, thus mitigating the effects of unequal access to high quality science courses in high school, for example.
Active learning, while beneficial for all students, also helps reduce the disparity in academic performance (i.e., the achievement gap) between different subpopulations of students. Haak et al. (71) showed that the incorporation of active learning via higher-order assignments (i.e., problem-solving and data analysis practices) in an introductory biology course improved the performances of all students, reducing the achievement gap between students from disadvantaged and non-disadvantaged backgrounds. However, the study further demonstrated that different student subpopulations benefit from active learning interventions differently depending on their personal and cultural backgrounds (71-73). By providing students with additional learning strategies, active learning classroom accommodate diverse student learning preferences (74).
In addition to enhancing academic outcomes, active learning also leads to changes in student study behaviors and perception. After the addition of active learning into an introductory STEM course, students reported that they spent more time studying for the course and were more likely to complete and appreciate the pre-lecture assignments (72). Other studies found that in-class active learning interventions increased participation by generating an environment of confidence and comfort (58), while enhancing the performance of underrepresented minority students (75).
Considerations and trade-offs when using active learning
A study with introductory biology classes published in 2011 (40) was a surprise to many in the STEM education community. The data showed that active learning interventions did not result in learning gains as previous studies have reported. The authors speculated that without rich pedagogical knowledge, the instructors did not use active learning interventions effectively (40). For instance, adding in-class exercises without reducing the lecture material could make the delivery of lectures cursory and shallow, which is the opposite of the purpose of active learning. Moreover, active learning interventions could be viewed as distractions when cognitive skills required in the exercises are not aligned with the skills that other assessments in class aim to develop.
Arguably the biggest cost when incorporating active learning is class time. Given that class time is limited, spending it on active learning interventions usually results in less coverage of material via lecture. Instructors can still expect students to cover all of the material, for example by providing study guides, practice tests, and reading assignments, and by assigning the tutorials available with their text. Additionally, when preparing for lectures or assignments with active learning elements, instructors have to invest significant time in identifying learning goals and designing questions and activities that engage students with the material beyond factual recall. (A good strategy is for the instructor to take the "punchline" from the lecture that they planned to present and turn it into one or more questions. For example, instead of explaining a graph, ask students to explain it.)
Some active learning interventions might (or are specifically designed to) take students out of their comfort zone. For instance, some active learning interventions force students to speak up in class and thus may alienate introverts who prefer quiet introspection. Certain active learning interventions might be inappropriate if the class contains students with disabilities or special needs. Therefore, some students might not appreciate these activities and instead prefer a more passive lecture. Furthermore, much like deciding the level of detail to pitch a traditional lecture, the level of required thinking for the active learning intervention could be too challenging or not challenging enough for a subpopulation of students in the class.
Active Learning Resources
Table 2 contains a selection of websites, including learning centers affiliated with universities, that are valuable resources for active learning interventions. This list is not meant to be all inclusive. We encourage readers to share their favorite resources using the "comments" tab on the article.
What do students think about active learning?
Surveys that explore student feedback on active learning found that the majority of students generally like active learning interventions and consider them as important tools for their academic performance (70,76-79). Interestingly, Welsh et al. (79) found significant differences by gender (with female students rating the active learning interventions more important than male students) and by year (upperclassmen rating the active learning interventions less important than first/second year students). Students report that they enjoy classes that use in class active learning more than traditional lectures (70). The authors of one study concluded that clicker questions seem to stimulate internal motivation by generating an interesting and engaging lecture environment (80). Students viewed clicker questions during lecture as a helpful way to reveal misconceptions and to give feedback to the instructor if the majority of the class did not understand a certain concept (79). Students also reported that instructors were more likely to go over challenging concepts again when seeing quantitative data of how many students did not understand the concepts rather than after asking the class "Who did not understand this?" (79).
In surveys regarding students' perspective of active learning, negative comments fell into three major categories: the activities wasted time; the questions were too easy or too hard; and the effectiveness of group discussions depended on the engagement of their fellow students (79). A recent study with medical students showed that, while the students were supportive of the general concept of active learning, they also expressed frustration about perceived inefficiencies (81).
Education research has collected convincing evidence for the benefits of active learning in different fields and student populations. Education researchers are now shifting their attention from asking if active learning works to how it works. Below, we briefly list some future considerations in the growing field of active learning, as well as a recent trend that may shape the landscape of higher education and demand revision of the current structure of active learning.
Future research on active learning
Freeman et al. (66) concluded their meta-analysis of active learning studies by proposing "second-generation research" on active learning. The focus of these future studies should be identifying attributes that significantly contribute to the positive outcome in active learning, such as the types of questions and the degree of student collaboration. Future studies should also compare different types of active learning interventions and determine the optimal settings in which active learning can lead to the best learning outcome (8).
The need for clearer understanding of how active learning interventions work is also apparent from a study that investigated 33 randomly-chosen college biology courses. The authors found that the frequency of active learning interventions is not correlated with student learning and cautioned that wrong implementation of active learning could nullify its potential to have a positive effect (40). To properly train educators in active learning pedagogy, the science education community needs to establish a "certified" tool box of active learning interventions and guidelines that enable easy adaption of the strategy to different fields and contexts. Detailed descriptions (e.g., which types of question work best in which student group) and "troubleshooting" suggestions will allow other teachers to adapt and improve new exercises.
The use of active learning within a course has been shown to increase long-term retention and deep learning (82-83). However, most studies focus on the use of one specific pedagogical tool and assess learning at the conclusion of the course or just few months later (84). Future studies should look at whether and how the use of active learning interventions make a difference in long term retention (e.g., 3-5 years) of information and/or skills, as well as engagement and persistence in STEM majors.
Most existing active learning interventions were designed to enhance student understanding of specific concepts introduced in class. Addressing the overall goal of higher education, instructors should also try to devise active learning interventions that can spur genuine interest in the subject and foster student motivation. Moreover, philosophical or psychological underpinnings of the effect of active learning interventions would be an interesting topic of interdisciplinary research.
Support for science educators
Instructor knowledge about metacognition and constructivism is a critical factor that links active learning interventions to improved academic achievement (5,8,40,85-86). Acknowledging the need for instructor training, science education communities have developed workshops for faculty and postdoctoral fellows (e.g., Summer Institutes on Scientific Teaching; http://www.summerinstitutes.org) (87) and active learning databases (Table 2). However, these efforts can still be increased. As mentioned above, detailed documentations and toolkits of the active learning interventions and centralized platforms for sharing active learning strategies and assessment tools will help instructors fully achieve the potential of active learning interventions.
Just as in every other field in today's world, the education community should be informed and trained in newly available technologies that can make learning more dynamic and personalized. For example, instead of using traditional clicker systems, educators can use web-based tools, such as Learning Catalytics (www.learningcatalytics.com), to increase accessibility and offer various types of questions. Educational games and lab simulations can also promote active learning and increase student learning (78,88).
With advances in both technology and educational research, it can be difficult for some faculty to stay abreast of the latest developments. Perhaps instructors should be encouraged to amass credits (via workshops and conferences) toward "Continuing Pedagogical Education" much as is the case for practicing physicians with Continuing Medical Education.
Active learning in the online learning era
The domain of active learning interventions is expanding to the online space. MOOCs, or massive open online courses, emerged as a force that some argued would revolutionize higher education. As the name indicates, MOOCs exclusively use the online platform to offer instructional materials. During their expansion, MOOCs innovated online pedagogy and triggered educational research in online learning (89-96). With an increasing number of courses incorporating online learning in the future, there should be a strong demand for active learning interventions that can be used in online courses.
SCIENTIFIC TEACHING THEMES
Active learning has taken center stage in undergraduate education. Students are no longer considered passive vessels that are mechanically filled with knowledge, but instead are challenged to play an active and autonomous role in their learning process. The successful and effective use of several active learning interventions has laid the groundwork for a more detailed investigation as to how these active learning interventions work and how instructors can apply them even more effectively to improve student learning. The evidence supporting the benefits of active learning and the resources available online should encourage instructors to incorporate these activities into the classroom.
We would like to dedicate this review to Rich Losick, whose early adoption of active learning in biology classes inspired us, as well as Eric Mazur who pioneered active learning interventions at Harvard College. We thank Dennis Sun for excellent help with figures. We are deeply grateful to Robin Wright and the reviewers for their thoughtful and helpful comments and ideas that greatly improved the manuscript. We apologize to those authors whose studies we could not cite.
Cho J, Yu NK, Choi JH, Sim SE, Kang SJ, Kwak C, Lee SW, Kim JI, Choi DI, Kim VN, et al. 2015. Multiple repressive mechanisms in the hippocampus during memory formation. Science 350:82-87.
American Association for the Advancement of Science. 2011. Vision and Change in Undergraduate Biology Education: A Call to Action. Washington, DC.
Gibbons A. 1994. A time of trials and tribulations. Science 266:844-851.
National Research Council. 1996. National Science Education Standards. Washington, DC: National Academies Press.
Allen D, Tanner K. 2005. Infusing active learning into the large-enrollment biology class: seven strategies, from the simple to complex. Cell Biol. Educ. 4:262-268.
Freeman S, Haak D, Wenderoth MP. 2011. Increased course structure improves performance in introductory biology. CBE Life Sci. Educ. 10:175-186.
Gardner J, Belland BR. 2012. A conceptual framework for organizing active learning experiences in biology instruction. J. Sci. Educ. Technol. 21:465-475.
Linton DL, Pangle WM, Wyatt KH, Powell KN, Sherwood RE. 2014. Identifying key features of effective active learning: the effects of writing and peer discussion. CBE Life Sci. Educ. 13:469-477.
Michael J. 2006. Where's the evidence that active learning works? Adv. Physiol. Educ. 30:159-167.
Prince M. 2004. Does active learning work? A review of the research. J. Eng. Educ. 93:223-231.
Collins JW, O'Brien NP. 2003. The Greenwood Dictionary of Education. Westport, CT: Greenwood.
Anthony G. 1996. Active learning in a constructivist framework. Educ. Stud. Math. 31:349-369.
Dewey J. 1916. Democracy and Education: An Introduction to the Philosophy of Education. New York, NY: The Macmillan Company.
Taylor PG. 2000. Changing expectations: preparing students for flexible learning. Int. J. Acad. Dev. 5:107-115.
Knight JK, Wood WB. 2005. Teaching more by lecturing less. Cell Biol. Educ. 4:298-310.
Reagan SB. 1988. Teaching TAs to teach: show, don't tell. W.P.A. 11:41-51.
DebBurman SK. 2002. Learning how scientists work: experiential research projects to promote cell biology learning and scientific process skills. Cell Biol. Educ. 1:154-172.
Gehring KM, Eastman DA. 2008. Information fluency for undergraduate biology majors: applications of inquiry-based learning in a developmental biology course. CBE Life Sci. Educ. 7:54-63.
Lents NH, Cifuentes OE, Carpi A. 2010. Teaching the process of molecular phylogeny and systematics: a multi-part inquiry-based exercise. CBE Life Sci. Educ. 9:513-523.
Odom DP, Grossel MJ. 2002. Using the two-hybrid screen in the classroom laboratory. Cell Biol. Educ. 1:43-62.
Bonwell CC, Eison JA. 1991. Active Learning: Creating Excitement in the Classroom. Washington, DC: George Washington University.
Hake RR. 1998. Interactive-engagement versus traditional methods: a six-thousand-student survey of mechanics test data for introductory physics courses. Am. J. Phys. 66:64-74.
Bloom BS. 1956. Taxonomy of Educational Objectives: The Classification of Educational Goals. New York: McKay.
Anderson LW, Krathwohl DR, Airasian PW, Cruikshank KA, Mayer RE, Pintrich PR, Raths J, Wittrock MC. 2001. A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives, Complete Edition. New York: Addison Wesley Longman.
Kyriacou C, Marshall S. 1989. The nature of active learning in secondary schools. Eval. Res. Educ. 3:1-5.
Noddings N. 1990. Constructivist Views on the Teaching and Learning of Mathematics. (RB Davis, CA Maher, and N Noddings, Eds.) Reston, VA: National Council of Teachers of Mathematics.
Jonassen DH. 1991. Objectivism versus constructivism: do we need a new philosophical paradigm? Educ. Technol. Res. Dev. 39:5-14.
Rodriguez V. 2012. The teaching brain and the end of the empty vessel. Mind Brain Educ. 6:177-185.
Ertmer PA, Newby TJ. 1993. Behaviorism, cognitivism, constructivism: comparing critical features from an instructional design perspective. Perform. Improv. Q. 6:50-72.
Liu CH, Matthews R. 2005. Vygotsky's philosophy: constructivism and its criticisms examined. Int. Educ. J. 6:386-399.
Piaget J. 1926. The Language and Thought of the Child. New York, NY: Harcourt Brace.
Prawat RS, Floden RE. 1994. Philosophical perspectives on constructivist views of learning. Educ. Psychol. 29:37-48.
Vygotsky LS. 1978. Mind in Society. Cambridge, MA: Harvard University Press.
King A. 1993. From sage on the stage to guide on the side. College Teaching 41:30-35.
Deslauriers L, Schelew E, Wieman C. 2011. Improved learning in a large-enrollment physics class. Science 332:862-864.
Kaefer T, Neuman SB, Pinkham AM. 2015. Pre-existing background knowledge influences socioeconomic differences in preschoolers' word learning and comprehension. Read. Psychol. 36:203-231.
Gagné RM. 1968. Contributions of learning to human development. Psychol. Rev. 75:177-191.
Lord TR. 1997. A comparison between traditional and constructivist teaching in college biology. Innov. High. Educ. 21:197-216.
Andrews TM, Leonard MJ, Colgrove CA, Kalinowski ST. 2011. Active learning not associated with student learning in a random sample of college biology courses. CBE Life Sci. Educ. 10:394-405.
Li S, Brophy SP. 2012. Learning through cognitive dissonance: engineering students use of "pseudo peer diagrams". Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. https://peer.asee.org/21642
Flavell JH. 1976. Metacognitive Aspects of Problem Solving. In The Nature of Intelligence, L Resnick, Ed. Hillsdale, NJ: Lawrence Erlbaum Associates.
Akturk AO, Sahin I. 2011. Literature review on metacognition and its measurement. Procedia Soc. Behav. Sci. 15:3731-3736.
Crouch CH, Mazur E. 2001. Peer instruction: ten years of experience and results. Am. J. Phys. 69:970-977.
Sampsel A. 2013. Finding the Effects of Think-Pair-Share on Student Confidence and Participation. Honors Undergraduate Student Research. Paper 28. http://scholarworks.bgsu.edu/honorsprojects.
Lombrozo T. 2006. The structure and function of explanations. Trends Cogn. Sci. 10:464-470.
Aleven VAWMM, Koedinger KR. 2002. An effective metacognitive strategy: learning by doing and explaining with a computer-based cognitive tutor. Cognitive Sci. 26:147-179.
Chi MTH, De Leeuw N, Chiu MH, LaVancher C. 1994. Eliciting self-explanations improves understanding. Cognitive Sci. 18:439-477.
Renkl A. 1997. Learning from worked-out examples: a study on individual differences. Cognitive Sci. 21:1-29.
Wong RMF, Lawson MJ, Keeves J. 2002. The effects of self-explanation training on students’ problem solving in high-school mathematics. Learn. Instr. 12:233-262.
Smith MK, Wood WB, Adams WK, Wieman C, Knight JK, Guild G, Su TT. 2009. Why peer discussion improves student performance on in-class concept questions. Science 323:122-124.
Angelo TA, Cross KP. 1993. Classroom Assessment Techniques: A Handbook for College Teachers, 2nd Ed. San Francisco: Jossey-Bass.
Freeman S, Eddy SL, McDonough M, Smith MK, Okoroafor N, Jordt H, Wenderoth MP. 2014. Active learning increases student performance in science, engineering, and mathematics. Proc. Natl. Acad. Sci. U.S.A. 111:8410-8415.
Drits-Esser D, Bass KM, Stark LA. 2014. Using small-scale randomized controlled trials to evaluate the efficacy of new curricular materials. CBE Life Sci. Educ. 13:593-601.
Jensen JL, Kummer TA, Godoy PDdM. 2015. Improvements from a flipped classroom may simply be the fruits of active learning. CBE Life Sci. Educ. 14:1-12.
Stockwell BR, Stockwell MS, Cennamo M, Jiang E. 2015. Blended learning improves science education. Cell 162:933-936.
Ernst H, Colthorpe K. 2007. The efficacy of interactive lecturing for students with diverse science backgrounds. Adv. Physiol. Educ. 31:41-44.
Haak DC, HilleRisLambers J, Pitre E, Freeman S. 2011. Increased structure and active learning reduce the achievement gap in introductory biology. Science 332:1213-1216.
Eddy SL, Hogan KA. 2014. Getting under the hood: how and for whom does increasing course structure work? CBE Life Sci. Educ. 13:453-468.
Kim HS. 2002. We talk, therefore we think? A cultural analysis of the effect of talking on thinking. J. Pers. Soc. Psychol. 83:828-842.
Jones SE. 2007. Reflections on the lecture: outmoded medium or instrument of inspiration? J. Furth. High. Educ. 31:397-406.
Snyder JJ, Sloane JD, Dunk RD, Wiles JR. 2016. Peer-led team learning helps minority students succeed. PLoS Biol. 14:e1002398.
Fox-Cardamone L, Rue S. 2003. Students’ responses to active-learning strategies: an examination of small-group and whole-class discussion. Res. Educ. Reform 8:3-15.
Long T, Logan J, Cummins J, Waugh M. 2016. Students’ and instructors’ attitudes and receptions of the viability of using a flipped classroom instructional model in a technology-enabled active learning (TEAL) classroom: a preliminary study. JoTLT 5:46-58.
Cavanagh AJ, Aragón OR, Chen X, Couch B, Durham M, Bobrownicki A, Hanauer DI, Graham MJ. 2016. Student buy-in to active learning in a college science course. CBE Life Sci. Educ. 15:ar76.
Welsh AJ. 2012. Exploring undergraduates’ perceptions of the use of active learning techniques in science lectures. J. College Sci. Teach. 42:80-87.
Trees AR, Jackson MH. 2007. The learning environment in clicker classrooms: student processes of learning and involvement in large university-level courses using student response systems. Learn. Media Technol. 32:21-40.
Walling A, Istas K, Bonaminio GA, Paolo AM, Fontes JD, Davis N, Berardo BA. 2016. Medical student perspectives of active learning: a focus group study. Teach. Learn. Med. 29:1-8.
Crossgrove K, Curran KL. 2008. Using clickers in nonmajors- and majors-level biology courses: student opinion, learning, and long-term retention of course material. CBE Life Sci. Educ. 7:146-154.
O’Day DH. 2007. The value of animations in biology teaching: a study of long-term memory retention. CBE Life Sci. Educ. 6:217-223.
Custers EJ. 2010. Long-term retention of basic science knowledge: a review study. Adv. Health Sci. Educ. Theory Pract. 15:109-128.
Turpen C, Finkelstein ND. 2009. Not all interactive engagement is the same: variations in physics professors’ implementation of peer instruction. Phys. Rev. S.T. Phys. Educ. Res. 5:020101.
Turpen C, Finkelstein ND. 2010. The construction of different classroom norms during peer instruction: students perceive differences. Phys. Rev. S.T. Phys. Educ. Res. 6:020123.
Wood WB, Handelsman J. 2004. Meeting report: the 2004 National Academies Summer Institute on Undergraduate Education in Biology. Cell Biol. Educ. 3:215-217.
Bonde MT, Makransky G, Wandall J, Larsen MV, Morsing M, Jarmer H, Sommer MO. 2014. Improving biotech education through gamified laboratory simulations. Nat. Biotechnol. 32:694-697.
Bali M. 2014. MOOC Pedagogy: gleaning good practice from existing MOOCs. MERLOT J. Online Learn. Teach. 10:44-56.
Comer DK, Clark CR, Canelas DA. 2014. Writing to learn and learning to write across the disciplines: peer-to-peer writing in introductory-level MOOCs. Int. Rev. Res. Open Dist. Learn. 15:26-82.
Guo PJ, Kim J, Rubin R. 2014. How Video Production Affects Student Engagement: An Empirical Study of MOOC Videos. In Proceedings of the First ACM Conference on Learning @ Scale Conference (L@S ’14). New York, NY: ACM.
Miller SL. 2015. Teaching an online pedagogy MOOC. MERLOT J. Online Learn. Teach. 11:104-119.
Ross J, Sinclair C, Knox J, Bayne S, Macleod H. 2014. Teacher experiences and academic identity: the missing components of MOOC pedagogy. MERLOT J. Online Learn. Teach. 10:57-69.
Rubens W. 2014. Improving the learning design of massive open online courses. Turk. Online J. Educ. Technol. 13:71-80.
Sandeen C. 2013. Integrating MOOCS into traditional higher education: the emerging “MOOC 3.0” era. Change Mag. High. Learn. 45:34-39.
Schoenack L. 2013. A new framework for massive open online courses (MOOCs). J. Adult Educ. 42:98-103.