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Articles |
*Department of Biology, Georgetown University, Washington, DC 20057; and Department of Education, Cornell University, Ithaca, NY 14853
Submitted March 27, 2009; Accepted May 28, 2009
Monitoring Editor: Debra Tomanek
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Although the proposed improvements noted above differ in detail, a remarkably consistent theme is the call to bring student-centered instructional strategies, such as active- and inquiry-oriented learning, into the classroom. Allen and Tanner (2005) define active learning as "seeking new information, organizing it in a way that is meaningful, and having the chance to explain it to others." This form of instruction emphasizes interactions with peers and instructors and involves a cycle of activity and feedback where students are given consistent opportunities to apply their learning in the classroom. By placing students at the center of instruction, this approach shifts the focus from teaching to learning and promotes a learning environment more amenable to the metacognitive development necessary for students to become independent and critical thinkers (Bransford et al., 2000). A substantial number of studies have shown that active-learning instructional approaches can lead to improved student attitudes (e.g., Marbach-Ad et al., 2001; Prince, 2004; Preszler et al., 2007) and increased learning outcomes (Ebert-May et al., 1997; Hake, 1998; Udovic et al., 2002; Knight and Wood, 2005; Freeman et al., 2007) relative to a standard lecture format.
The establishment of several national programs that promote active-learning pedagogy (The National Academies Summer Institutes1 and FIRST II2), the establishment of journals such as CBE—Life Sciences Education, and the growth of several database repositories of active-learning exercises (MERLOT pedagogy portal3, TIEE4, FIRST II, National Digital Science Library,5 and especially BioSciEdNet6 and SENCER Digital Libary7) are all positive evidence of concerted responses to the calls for change noted above. These resources also provide significant support for faculty committed to implementing active-learning strategies in their courses both in terms of training opportunities and by making example teaching materials readily available. Nevertheless, the proposition of restructuring a large introductory course to emphasize elements of active learning can seem overwhelming for faculty with extensive time commitments in other realms and little or no formal training in pedagogy.
Here, we describe the development and implementation of an instructional design that focused on bringing multiple forms of active-learning and student-centered pedagogies into a traditionally lecture-based introductory biology course. Our course restructuring was motivated by several perceived deficiencies common to traditional lecture-based introductory courses. The most pronounced concern, shared by multiple faculty involved in the course, was poor student attitudes. Both numeric and written responses on course evaluations indicated that students were not satisfied with the course and did not recognize the importance of the course content to their education as biologists. For example, students often commented on course evaluations that the lectures and/or course materials were "boring." Furthermore, individual instructor–student interactions often indicated that students were more concerned with their test scores than with gaining a thorough understanding of the course material. Poor student attitudes also were reflected by poor attendance, limited participation in class, and suboptimal student performance.
We hypothesized that incorporating active-learning and student-centered pedagogy into the instructional design of our course would both improve student attitudes and also lead to increased student performance (Weimer, 2002). We chose to focus primarily on using problem-based learning activities because these activities tend to be more succinct and less open-ended than case-based activities, and thus it was easier to integrate problem-based activities into our previously established lecture organization. Our positive results illustrate how changing the instructional design of a course, without wholesale changes to course content, can lead to improved student attitudes and performance. The goals of this article are to 1) describe the elements of our instructional design that contributed to improved student attitudes and performance; and 2) discuss significant future challenges, so that other educators can learn from our experiences.
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MATERIALS AND METHODS |
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Course Description
Introductory Biology II is the second semester of a 1-yr sequence required for biology majors and premedical students. The first semester of the sequence, Introductory Biology I, focuses on molecular and cellular biology with some treatment of development and physiology. Introductory Biology II emphasizes principles of ecology, evolution, and a survey of the diversity of life. This basic course content was not changed substantially as part of the revision we describe, although we modified the order in which the material was presented (see below). In all 3 years, the lectures consisted of three 70-min periods per week. There also was an optional weekly recitation section where the instructor was available to answer student questions. In all 3 years (2006–2008), we handed out a set of questions ("the daily dozen") for each lecture to help guide students in their assigned textbook reading, and discussion in recitation often centered on these questions. Before our course revision, assessment for the lecture portion of the course consisted of three midterms and a final examination, with each exam consisting of a mix of quantitative problem solving, short answer, and short essay questions. As part of our course revision, we modified this assessment plan to include 10 weekly quizzes, two midterms, and a final exam. In all 3 years, all students were required to enroll in a weekly 3-h laboratory section that was assessed and evaluated separately from the lecture portion of the course. The laboratory portion of the course was not a part of this course revision.
Course Redesign
Our course redesign consisted of three major elements:
75% of all clicker questions presented over the entire semester (approximately 120 total questions each year), regardless of whether their answers were correct. Clickers were also used to administer weekly quizzes (see below).
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Data Analysis
We tested for differences in class composition between years based on categories in Table 4 by using a 
2 goodness-of-fit test. We tested for differences in Likert-scale student responses concerning attitudes toward the course from both the questionnaire and university course evaluations by using one-way analysis of variance (ANOVA) followed by a posteriori comparison of means with a sequential Bonferroni correction to control for experiment-wise error (
= 0.05). We used a one-way ANOVA of Likert-scale ratings of the helpfulness of different lecture components (i.e., weekly quizzes, clickers, etc.) with lecture component as a fixed effect and students nested within lecture component as a random effect. The one-way ANOVA was followed by planned (a priori) comparisons of means of different lecture components (averaged across years) with Bonferroni correction for multiple comparisons. We tested for differences between years (2007 and 2008) for each individual lecture component with a Student's t test, again with Bonferroni correction for multiple comparisons. To test for differences in student performance on identical final exam questions among years (2006, 2007, and 2008), we also used one-way ANOVA and a posteriori comparison of means with Bonferroni correction. To test for differences in performance on the entire final exam in 2006, 2007, and 2008, we performed one-way ANOVA on square-root arcsine-transformed percentage scores in each year followed by a posteriori comparison of means with Bonferroni correction.
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Categories were developed in relation to code frequencies as determined by the number of students whose statements were tagged with that code in a given year. In this way, we avoided overestimating a code's frequency when, for example, an individual mentioned a lecture element multiple times. The most frequently used codes (e.g., clickers and quizzes) were elevated to category status. Text tagged with these codes were re-examined for the explanatory details (subcodes) that are presented associated with each category in Tables 5 and 6.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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2 = 11.21, df = 7, p > 0.10).
Student Attitudes
All measures of student satisfaction differed significantly between years (Figure 1). These measures include change in interest in the course material from the start to the end of the semester (F2409 = 5.22, p < 0.001), ranking of relevance of course material to long-term student goals (F2407 = 6.65, p = 0.001), self-reported student learning (F2355 = 11.70, p < 0.001), ranking of classroom presentations as stimulating (F2358 = 26.52, p < 0.001), ranking of the course as challenging (F2355 = 15.87, p < 0.001), and overall evaluation of instructor (F2355 = 15.87, p < 0.001). For all measures of student satisfaction, a posteriori comparison of treatment means indicated that student satisfaction was significantly higher in 2007 and 2008 than in 2006 (sequential Bonferroni, p < 0.05) but did not differ between 2007 and 2008 (p > 0.05; Figure 1). A summary of student free responses to questions probing student satisfaction and dissatisfaction in all 3 years is provided in Tables 5 and 6, respectively.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Student Attitudes
The data in Figure 1 clearly indicate that the changes we implemented in 2007 and 2008 improved student attitudes toward the course. For every question considered, student satisfaction scores increased significantly between 2006 and 2007 and did not differ between 2007 and 2008. It is important to note that in 2006, the first author was teaching this course for the third consecutive year. University teaching evaluation scores were consistent in the three years before 2007, and in fact a major reason for implementing the changes we describe in 2007 was that the instructor (first author) felt strongly that after 3 years, additional teaching experience alone was unlikely to cause a significant change in student response to the course. We therefore attribute the clear and consistent changes in student attitudes between 2006 and 2007 (Figure 1) directly to the elements of course redesign we describe here, and the similarity of student responses in 2007 and 2008 (Figure 1 and Tables 5 and 6) further supports this interpretation.
The students' free-responses summarized in Tables 5 and 6 are consistent with the data presented in Figure 1. First, it should be noted that the proportion of positive comments increased from 2006 (65%) to 2007 (81%) and 2008 (89%). In 2006, the top category (56%) of positive response concerned traditional course material (e.g., PowerPoint slides, videos), whereas in 2007 and 2008 traditional course materials were mentioned in only 10–11% of the positive comments, and quality of instruction was the most common positive comment in both years at 24 and 27%, respectively (Table 5). Together, these results clearly indicate that students' perception of the quality of instruction increased in 2007 and 2008, similar to results in Figure 1.
Student-centered and Active-Learning Components
Students' positive free-response answers explicitly referencing specific components of the course redesign were the second (14%) and third (13%) most frequent category of positive response in 2007, and second (16%) and fourth (12%) most frequent category of positive response in 2008 (Table 5). These comments in 2007 and 2008 that specifically mention the active-learning and student-centered pedagogy we introduced in 2007 included references to "engagement," "immediate feedback," and "multiple approaches to learning." There were almost none of these specific references in 2006.
With respect to negative free responses (Table 6), in 2006 the most frequent category of response was that lecture was not stimulating (25%), whereas in 2007 and 2008 that category composed <1% of the negative responses. Again, these data corroborate the results in Figure 1, where lecture was ranked as more stimulating in 2007 and 2008 than in 2006.
It is important to note, however, that two specific elements of our course redesign were explicitly mentioned as the first (group work, 17%) and second (weekly quizzes, 15%) most frequent category of negative response in both 2007 and 2008. Group work was also ranked relatively low in terms of helpfulness to student learning (Figure 2). Our interpretation of the feedback on group work is that we need to further refine this element of the course. We adopted strategies for effectively implementing group work as discussed by Handelsman et al. (2007) and Ebert-May and Hodder (2008). Students did not receive credit for these in-class active-learning exercises, but the requirement to report out to the class seemed to provide a strong incentive for most students to engage seriously in these activities. During each group-work exercise the instructor would move throughout the classroom to monitor group progress, and it was rare to find a group that was not seriously engaged in the exercise. However, the attempt to include a group exercise in almost every lecture meant that both the quality and rigor of exercises varied considerably. The group exercises that elicited the most animated student participation were those that were sufficiently challenging that very few students could solve the problem individually, but at least 50% or more of the groups could solve the problem by working as a team. Some of our most active group interactions occurred when we administered a challenging quiz, and then immediately allowed the students to retake the quiz as a group with the stipulation that the students would receive the highest of either their group or individual scores. This consideration suggests that a potential modification to further increase engagement in the group work would be to assign points to these in-class exercises (Ebert-May and Hodder, 2008).
Our interpretation of the relatively high proportion of negative comments regarding the weekly quizzes (Table 6) differs from that regarding the group work. The weekly quizzes were implemented in order to encourage students to keep up with the course material and to provide them with regular feedback on their understanding of the material in a low-stakes assessment environment. Note that in Figure 2 students ranked the weekly quizzes third highest in terms of helpfulness in both 2007 and 2008. We thus interpret the data in Table 6 and Figure 2 to indicate that although some students may dislike the weekly quizzes (administered at 8:50 AM), many recognized that these quizzes were helpful to their learning. Sixty-four percent of the respondents rated quizzes at 4 or 5 in terms of their helpfulness. The following quote is a typical comment made by students who rated quizzes at 4 or 5:
"Quizzes seemed like a hassle at first but in the end when our exams came up, since I had been studying all along for the quizzes, I had learned/studied most of the material, so I actually appreciate the weekly quiz system." S136.2008.Q3B
We view these results as positive evidence of metacognitive awareness (Bransford et al., 2000) in that the weekly quizzes seem to have helped these students identify strategies for enhancing their own learning. This represents a particularly important goal for introductory classes that aim to prepare students for more advanced course work and independent learning.
Figure 2 indicates considerable consistency between 2007 and 2008 in the ranking of various lecture elements in terms of the helpfulness to student learning. The explicit learning goals (Table 3) ranked highest in both years (Figure 2). From a student's perspective, learning goals establish clear expectations about what skills and content students should master from each lecture. From an instructor's perspective, learning goals play a critical role in shaping both instructional activities and assessment through the process of "backward design" (Wiggins and McTighe, 1998; Handelsman et al., 2007), whereby learning goals explicitly articulate the desired learning outcomes to both instructor and students. Those desired outcomes then specify the assessment tasks that determine whether the desired outcomes have been met, and also shape teaching activities required to meet the desired goals. During 2007 and 2008, through the process of backward design, the learning goals provided a clear "road map" for both determining the content and organization of lectures and also for writing exams, whereas in 2006 both processes took place in a much less structured manner.
The personal response system (clickers) ranked the second highest in terms of helpfulness with learning in both 2007 and 2008 (Figure 2). These results are consistent with those of a large number of previous studies documenting positive student responses to clicker systems (for review, see Judson and Sawada, 2002) and a large body of evidence indicating that the use of clickers and associated peer interaction (see below) can lead to improved student learning (Crouch and Mazur, 2001; Knight and Wood, 2005; Preszler et al., 2007; Smith et al., 2009). In a recent and intriguing study from physics, Reay et al. (2008) found that the use of clickers not only led to increased learning gains in an introductory physics course but also seemed to reduce the performance difference between males and females.
The clickers were an effective pedagogical tool in our introductory biology course in several respects. First, the clicker system provided "real-time feedback" to the students (Table 5). This feedback allowed the instructor to establish clear expectations regarding the depth of student understanding required to answer quiz and exam questions correctly. Simultaneously, this information allowed students to gauge their understanding continually relative to those expectations (i.e., formative assessment). The clickers were also extremely helpful in identifying, and thus allowing us to rectify, by addressing in a more direct and thorough manner, student misconceptions. Two striking misconceptions in our class concerned the ability to interpret a phylogenetic tree (see the "tree thinking" exercise by Baum et al., 2005) and the failure to recognize that photosynthetic organisms not only fix CO2 through photosynthesis but also release CO2 through cellular respiration (Wilson et al., 2006).
The clickers were also very useful in initiating peer instruction in the classroom (Mazur, 1997; Crouch and Mazur, 2001). This occurred when between 35 and 75% of the class answered a clicker question incorrectly, and students were then instructed to consult with a neighbor for 1 to 2 min to discuss their answers. The students were then repolled without being informed of the correct answers. Such occasions invariably led to animated discussion among the students in the class, and almost always resulted in an increase in the proportion of correct answers when the students were repolled. The clicker questions that generated the most animated student discussion were those that either did not have a single correct answer or that elicited a relatively even number of responses between two or more answers. These results are consistent with previous studies that demonstrate the efficacy of peer instruction facilitated by clickers to promote student learning (Crouch and Mazur, 2001; Freeman et al., 2007; Smith et al., 2009). However, it is critical to recognize that it is the peer interaction rather than the clickers per se that promotes student learning (Smith et al., 2009), emphasizing that an appropriate underlying pedagogical design is essential for the effective use of clickers (Mazur, 1997; Crouch and Mazur, 2001).
Student ranking of helpfulness for the vocabulary list and recitation increased significantly from 2007 to 2008 (Figure 2). Notably, these components were ranked relatively low in 2007 and this feedback from the student questionnaire in 2007 enabled us to target these aspects of the course design in 2008. The vocabulary list presented at the beginning of each class (see Course Redesign) was ranked as the least helpful element of the lecture in 2007. The goal of these lists was to help students use technical terminology to formulate concise and precise answers to free-response questions on exams. In 2008 we discussed this goal in lecture and explicitly modeled the process several times. In the future, we plan to develop active-learning exercises that explicitly focus on clear written communication.
The increase in helpfulness ranking from 2007 to 2008 for the optional recitation session (Figure 2) was particularly notable. Based on student feedback in 2007, in 2008 we moved the quizzes to Thursday so that they were given the day immediately after the recitation sessions. Attendance at the recitation sessions increased dramatically, consistent with the data in Figure 2. This change from 2007 to 2008 provides an excellent example of how student feedback can be used to make simple changes that have a large impact on student satisfaction and performance.
Finally, we note that one of the major elements from the course in 2006 that was carried over into 2007 and 2008 was the daily dozen (a list of questions designed to help students identify important concepts in the textbook reading assignments), which ranked relatively low in terms of helpfulness compared with elements that were introduced as part of our course restructuring in 2007. We did not receive specific positive or negative feedback regarding the daily dozen on our questionnaire in 2006–2008 (Tables 5 and 6), and we attribute the relatively low ranking of this component in 2007 and 2008 (Figure 2) to greater enthusiasm for other components of the course.
Student Performance
Our data on academic performance are consistent with previous studies indicating that student-centered pedagogy and interactive-learning activities increase student performance (Ebert-May et al., 1997; Udovic et al., 2002; Knight and Wood, 2005; Freeman et al., 2007; Walker et al., 2008). The data in Figure 3 illustrate student performance on identical final exam questions administered in all 3 years and show consistent increases in performance between 2006 and 2008. Furthermore, the proportion of points on the final exam for questions at higher levels of Bloom's taxonomy (levels 3–4, application-analysis) increased from 15–18% in 2006–2007 to 25% in 2008. Furthermore, the average student performance on the final exam also increased in 2008 (91%) relative to 2006 (86%) and 2007 (85%). Together, these results indicate increased academic performance and imply increased proficiency with higher-order problem-solving skills associated with the changes in instructional design implemented in our course. These conclusions are somewhat conservative because the 2006 final exam contained a section in which students were allowed to choose six of eight questions to answer, but students were not given any choices on the 2007 and 2008 final exams.
The results on student performance noted above suggest that the most pronounced increases in performance occurred between 2007 and 2008, whereas results in Figure 1 and Table 5 indicate that student attitudes increased significantly from 2006 to 2007 and did not change between 2007 and 2008. We believe these results indicate that a semester of experience with implementing the active-learning and student-centered pedagogies in 2007 made these approaches more effective in improving student performance in 2008. Although the initial goal of our course redesign was to target student attitudes, we are now initiating more intensive efforts to quantify student learning by using pre- and postcourse assessment tools, assessment of higher-order skills such as the interpretation of primary literature, and performance on the Biology GRE.
Institutional Context
The course redesign we implemented required a significant time investment both in the approximately 6 mo leading up to 2007, and during the first semester of implementation. Attendance at a national workshop, the National Academies Summer Institutes on Undergraduate Education in Biology (www.academiessummerinstitute.org/) provided significant background theory and training. Also, in fall 2006, we convened a series of on-campus seminars featuring national leaders in science education (http://cndls.georgetown.edu/events/symposia/TFU/). These seminars were particularly useful both in generating support from our departmental colleagues to implement changes in a course that is foundational to the department's curriculum and also in providing the opportunity to discuss specific details of course redesign with individuals highly experienced in implementing active-learning and student-centered pedagogical approaches. It is important to note, however, that once the initial course redesign was implemented in 2007, teaching the course in 2008 did not require a significant additional time commitment relative to 2006 (before our changes were implemented) and yet the increased positive student response to the course was sustained (Figure 1 and Table 5). Furthermore, the improved scores on the university-administered course evaluations (see questions 2–6 in Figure 1), the primary mechanisms of assessing teaching at most institutions, indicates that the time investment required to implement a course restructuring can have a positive impact on instructor evaluation criteria.
Finally, the course redesign had another unanticipated benefit: it improved not only the students' attitude toward the course but also the instructor's morale and enthusiasm. Introductory Biology II has long been a problematic course for our department because of deficiencies noted in the Introduction (poor student attitudes, passive [superficial] learning, and suboptimal student performance). As a consequence, instructors often lose enthusiasm for teaching this course after 2 to 3 years. However, the interactive pedagogy and positive student responses made this a much more exciting and rewarding course to teach in 2007 and 2008.
The changes we implemented also have had an impact at the departmental level. Based in part on the positive student reactions to interactive and student-centered pedagogy in Introductory Biology II, four instructors have implemented the use of clickers in their courses and one faculty member attended the 2007 National Academies Summer Institutes on Undergraduate Education in Biology.
In summary, we developed and implemented an instructional design that focused on incorporating active-learning and student-centered pedagogy into what was previously a traditional lecture-based introductory biology course. These changes led to sustainable improvements in student attitudes and performance. Although the changes we implemented required a significant time commitment in the first year (2007), this was essentially a "one time investment" because it did not require extra effort to teach the course using the revised model in 2008. Furthermore, several faculty in our department have begun to incorporate interactive and student-centered pedagogies into their courses. The course reorganization we describe thus not only provides a model for revision of an individual course but can also provide a catalyst for institutional reform.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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2 http://first2.plantbiology.msu.edu//.
3 http://pedagogy.merlot.org/.
6 www.biosciednet.org/portal/.
Address correspondence to: Peter Armbruster (paa9{at}georgetown.edu)
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| HOME | HELP | FEEDBACK | ARCHIVE | SEARCH | TABLE OF CONTENTS |
) and 2008 (
). Lecture components as described in text: clicker = clicker questions; quiz = weekly quizzes; lgoal = learning goals; vocab = vocabulary lists; group = group work in class; daildoz = daily dozen reading questions; recit = optional weekly recitation section; and stdygrp = optional study group outside class. Results of one-way ANOVA testing for differences among lecture components was highly significant (p < 0.001). The legend on the top indicates results of planned comparisons (A) among components (pooled across years) where components that share the same letter are not significantly different (p> 0.05) and (B) between years (2007 and 2008) for each individual component, where * indicates p < 0.05, ns indicates p > 0.05.