Comparison of student performance in cooperative learning and traditional lecture-based biochemistry classes

Authors


Abstract

Student performance in two different introductory biochemistry curricula are compared based on standardized testing of student content knowledge, problem-solving skills, and student opinions about the courses. One curriculum was used in four traditional, lecture-based classes (n = 381 students), whereas the second curriculum was used in two cooperative learning classes (n = 39 students). Students in the cooperative learning classes not only performed at a level above their peers in standardized testing of content knowledge and in critical thinking and problem-solving tasks (p < 0.05), but they also were more positive about their learning experience. The testing data are in contrast to much of the medical school literature on the performance of students in problem-based learning (PBL) curricula, which shows little effect of the curricular format on student exam scores. The reason for the improvement is undoubtedly multifactorial. We argue that the enhancement of student performance in this study is related to: 1) the use of peer educational assistants, 2) an authentic PBL format, and 3) the application of a multicontextual learning environment in the curricular design. Though educationally successful, the cooperative learning classes as described in this study were too resource intensive to continue; however, we are exploring incorporation of some of the “high context” aspects of the small-group interactions into our current lecture-based course with the addition of on-line PBL cases.

Traditionally, introductory biochemistry classes for undergraduate nonmajors are taught in lecture format. At our institution, because of a large student population and small faculty size, such classes range from 100 to 200 students. Although different learning resources are available, and there are several faculty office hours scheduled each week, both student performance and satisfaction with the course vary widely. Typically, students are not engaged in the course and tend to rely on short-term memorization strategies rather than learning the material with understanding. Different techniques have been attempted to engage the students in lecture-based courses, and for the most part in the authors' experiences these techniques, although marginally successful, have not made a significant impact on either student performance or their approach to the subject.

An additional issue that affects student learning at our institution is the presence of a large population of students with different learning styles. Each class has a relatively high population of minority students, older students, and students returning to the classroom after a 3- to 10-year absence. In his monograph on cultural diversity [1], Ibarra has described the academic challenges faced by these students. His contention is that providing only one format for instruction puts any student into a nonoptimal learning environment. Based on a set of dynamic principles of cultural context and cognition, Ibarra has proposed a context diversity model, called multicontextuality, for changing the academic culture and learning environment. This new paradigm of diversity explains how the composite of a person's experience throughout his/her life affects performance in higher education. It is framed around the idea that people are imprinted from birth to maturity by the kinds of learning interactions they encounter within their communities. These events differ significantly from each other and from the kinds of experiences that are normally encountered in a homogeneous university system, especially in lecture intensive science, technology, engineering, and math disciplines. In brief, the environment in which an individual develops encompasses a continuum of interpersonal interactions that range from what Ibarra terms “low context” to “high context.” A low context learning environment is one in which there is little opportunity for discussion or debate such as a formal lecture, whereas in a high context environment communication is more dependent on the global characteristics of the communication. An interactive small group problem-solving session would be considered an example of a high context learning environment. Multicontextuality implies that a learning interaction that is solely centered in one style will provide suboptimal learning for individuals of different contextual patterns. Recognized as a unique approach for enhancing diversity in science, technology, engineering, and math fields [2], multicontextuality addresses issues particularly evident in the western and southwestern regions of the country and requires that in these regions the nature of the undergraduate curriculum reflect the diverse population of the learners.

Problem-based learning (PBL)11 and cooperative learning methods have been described as increasing student engagement in a subject [37]. Moreover, these instructional strategies are also consistent with the multicontextuality model of education. This article compares the results of student performance in two different styles of introductory biochemistry classes. One set of classes utilized small group cooperative learning pedagogy, whereas the second set of classes consisted of traditional lecture-based presentations. Students in both cooperative learning and traditional courses were evaluated using similar assessment instruments. Based on our previous experience in medical education at this institution [8, 9], we hypothesized that an inquiry-based collaborative learning instructional strategy would not hurt student performance on standardized biochemistry examinations and would engage a larger population of students.

MATERIALS AND METHODS

Design of the Cooperative Learning Course—

The cooperative learning classes were split into tutorial groups of five to six students, each meeting in a small room for 1 h per session. These classes met for the same total number of hours per semester as did the traditional lecture-based classes. Each tutorial group included a senior biochemistry major or first year graduate student as an educational assistant (EA). Faculty members met with these EAs on a weekly basis to discuss the educational approach used in this course and the theory supporting this approach as well as to review the biochemical concepts that would be discussed by the students in the coming week. The EAs were instructed not to lecture to the students but rather to push them to find the limits of their understanding. They were also charged with providing nongraded constructive feedback to the class participants. EAs were provided training in verbal assessment and practiced on each other and the faculty during the weekly meetings. Table I lists the basic instructions given to the EAs describing what they were trying to accomplish during the small group meetings. Each item in this list, derived from the National Research Council monograph How People Learn [10], was discussed in depth with the EAs during the weekly meetings. The use of undergraduate students and the effect of their participation on each other, the faculty, and the individual student are the subjects of the accompanying article and will not be further elaborated here.

PBL encompasses several different learning environments that range from teacher led case discussions to an independent discovery, inquiry-based learning format. Barrows [11] has described the adverse effect that this wide spectrum of definitions has on attempts to evaluate curricular changes and suggests that for any comparison of a cooperative learning curriculum with a standard lecture format there needs to be well defined criteria for the nature of the curricular structure. A lack of consensus about the definition of PBL, clearly evident at our school [12], may be the reason for many divergent statements in the literature comparing PBL and other cooperative learning techniques with more traditional instructional methods.

To standardize the nature of the cooperative learning environment in our small groups, we followed the PBL description of Greenwald [13]. A problem scenario introduced the learning objectives. However, problem scenarios were vague, requiring students to discuss the cases fully in order to identify the information that they needed to understand the problem. Students then researched the problem and explained the solution using biochemistry concepts discussed at the level of detail used in the classical lecture-based biochemistry class. This procedure required students to initially confront their own understanding and ideas about the biochemistry concepts under discussion and then compare their understanding with that of the other students in the group. It should be noted that this highly interactive inquiry-based learning style is consistent with what Ibarra has described as a “high context” learning environment in contrast to the “low context” learning environment of the typical lecture.

The cases progressed following a successive reveal, guided discovery format. This level of instructor guidance was selected both to minimize any differences between groups and to provide the EAs with an idea about what to expect as the cases unfold. Moreover, in our experience, student discussions tend to become too vague or shallow if left without some guidelines to model the depth of understanding required.

Course Content—

The instructional content for this cooperative learning course was determined by the content in the traditional lecture-based, one-semester biochemistry course. To design the cases, the sequence of topics in the traditional course was used as the guide, and biochemistry questions or scenarios were written that could integrate several different concepts. In addition to mirroring the conventional course content, every effort was made to integrate material from the students' other courses and current science topics appearing in the public media. To understand the cases and their solutions required that students understand the molecular basis of the situation. For example, students were presented with an individual who fainted when he was taken to a high altitude. This condition, which eventually turned out to be a case of sickle cell anemia, required students to discuss and understand ligand-binding behavior in proteins, oxygen transport, all levels of protein structure, and methods of protein isolation and analysis, all topics in the traditional lecture-based course.

Table II compares the didactic content of the two courses. From Table II it is evident that not all of the material in the traditional course could be easily fit into the case studies. To accommodate this subject matter, topic-specific lectures were also presented. The balance between lecture and cases consisted of ∼80% small group cooperative learning and 20% lecture. The lectures, however, were not the traditional 50-min monologues. These periods were more appropriately described as an open discussion between the faculty, EAs, and the students.

Because there was only a limited amount of class time available, and because this guided discovery learning modality was new to the students, similar successive reveal problems were provided on the computer for additional practice. New concepts or content were not introduced with these electronic cases; rather, these additional cases allowed students practice in extending their new knowledge and applying concepts from the prototypical tutorial cases to a new situation. Student use of the electronic cases was entirely voluntary. These electronic cases were also available to the students in the traditional lecture-based biochemistry course.

Student Population—

Students participating in both the cooperative learning and traditional courses were juniors and seniors in college. All students had previously completed organic chemistry. The most common majors identified by the students were biology, pre-medicine, and pre-pharmacy. None of the students were biochemistry majors.

The first time the cooperative learning course was offered, students were not aware of its unconventional setup. The second time it was offered, all students registering knew that the course was not taught with standard lecture format. However, in both cases it was the only biochemistry course available during that semester. Though the students self-selected into the cooperative learning courses, the population of students in these smaller classes was the same in terms of student age, gender, major, and college distribution found in the traditional lecture-based biochemistry course. Ethnicity data and student GPA information are not available for either the traditional or cooperative learning course.

Student Assessment—

The traditional biochemistry course and the cooperative learning course were both divided into four different content sections. At the end of each of these sections, an exam was given. Each exam consisted of ∼30% multiple choice questions, 40% short answer essay questions and chemical reactions, and 30% critical thinking and problem-solving scenarios. Questions were all randomly selected from the same large question database. The question database was available for all students, in both courses, to use in their self-study. The size of the database is large enough that students cannot pass the tests simply by memorizing a limited number of questions and answers without understanding the concepts. The exams were considered by the participating faculty to be of comparable difficulty.

In addition to the written examinations, the cooperative learning class received performance feedback from the educational assistants at each of the class sessions. This feedback was not incorporated into a class grade but was intended for student formative development.

Course Evaluation—

The cooperative learning course was evaluated first and foremost by monitoring student performance on the exams. In addition, the instructors of record (W. A. and M. O.) and an independent faculty member (S. M.), who is a recognized institutional expert in PBL methodology, routinely observed the small group meetings, evaluated the cases, and talked with both EAs and students about their perceptions of the course. This was done in the context of the small group discussion as a means to both model a metacognitive approach to assessment as well as to collect student opinions. Finally, anonymous written student opinions about their experience and learning in this course were collected.

RESULTS

Development of Small Group Skills—

The tutorial progression and development of small group skills by the students were very similar to that observed with medical school students in PBL tutorial groups at this institution. Initially, there was student apprehension about the different type of learning required; however, the group as a whole became more cohesive and involved as the course progressed. Variability of individuals within the groups soon became apparent with leaders, introverts, and extroverts identified. Similarly, students who were solely present for the grade instead of the learning were rapidly identified by both faculty and peers. It was judged that the overall progression of the small group dynamic was independent of level or discipline (i.e. undergraduate biochemistry versus medical school), and as observed with medical students, dealing with the uncertainty of what one “needs to know” was difficult and one of the more disconcerting aspects for the students.

Student Performance—

Biochemistry knowledge was assessed after the end of each of the four major sections of the course. Table III shows the average scores for these four exams for both the conventional lecture-based classes and the cooperative learning classes. The consistency of exam construction from semester to semester is evident from the similar range in average scores from the traditional classes. These data also indicate a consistently higher performance for students in the cooperative learning classes and suggests that their overall understanding of the biochemistry concepts that were tested on the exams is comparable to if not better than that of students participating in the lecture classes.

Fig. 1 compares the distribution of student final numerical grades for the conventional classes and the cooperative learning classes. Final grades were determined on the basis of a student's three best exam scores and a final exam. These data, interestingly, show that the range in student scores is comparable for both groups of students with a similar percentage of students at both the high end and the low end of the distribution. Consequently, these data suggest that the performance of students who either easily master the material or do not really master the material at all remains unaffected by the nature of the instruction. It is the students in the middle of the distribution who appear to be more affected by the nature of the instruction. In this case, there is a consistent and significant (p < 0.05) improvement in performance for students participating in the cooperative learning classes. When the data are disaggregated and individual classes analyzed, similar results are observed (data not shown).

Traditionally, students in the lecture-based classes perform very poorly on scenario-type questions that require them to analyze data and come to a conclusion instead of simply recalling fact. Because students in the cooperative learning classes received much more practice in this activity during the group meetings, it was hypothesized that their performance would be superior to that of students in the conventional curriculum. To evaluate this possibility, students in two traditional and one cooperative learning class were presented with a medical scenario. They were required to evaluate a data set that included the results of a glucose tolerance test along with values for other serum metabolites and come to a conclusion about the nature of the patient's problem (which was a defect in gluconeogenesis). This scenario was initially constructed as an assessment of problem-solving skills for first year medical students, and the grading rubrics used were developed by clinicians external to the Department of Biochemistry. This scenario was also incorporated as a component of the exit evaluation for biochemistry majors. Biochemistry faculty, who had not been involved in question construction, provided their answers to the scenario during the initial standards-setting exercise in the development of this question. Identical grading rubrics were applied to all groups challenging the question. The grading rubrics for this question simply defined passing criteria and did not distinguish further between levels of achievement. Consequently, the data for this specific analysis simply indicate the percentage of students passing the question. The performance of different groups on this question is shown in Table IV. Students in the two types of introductory biochemistry classes performed quite differently on this critical thinking question. The performance of students in the cooperative learning class was significantly (p < 0.05) enhanced over students in the conventional class.

Student Opinion—

To understand the student response to the different curricular formats, students were interviewed and were asked to complete anonymous course evaluations. In both semesters, the students' initial attitude to the cooperative learning format was one of caution and discomfort. Comments from students indicated that this was something new to them. Students saw cooperative learning as harder because it put more of the learning burden on them and required student to student communication. The students needed to be continually reassured that they were learning what they were supposed to be learning. They also expressed a lack of confidence in the materials contributed by other students. By the end of the semester, the vast majority of the students stated that they enjoyed the cooperative learning experience. Many comments indicated that the students were learning with understanding and felt empowered by their learning. Students also saw the faculty more in the role of learning coaches rather than learning antagonists. Generally, student comments were extremely positive about the experience.

Probably the best indication of positive student opinion about the course became apparent the second time that the course was offered. The first time that the cooperative learning course was offered, the course remained open for registration up until the first day of class and did not fill to capacity. The second time that the course was offered, it was filled 4 h after registration began, and there was a waiting list of more than 50 students.

In both semesters that the cooperative learning course was offered, there was a smaller group of students, ∼10% of the class, who were dissatisfied with the experience. The most consistent sentiment from the dissatisfied students was that learning this way was harder because they were personally responsible for learning the material. Some students also felt that they did not get adequate return for their tuition because they paid for lectures and for the faculty to supply them with the information, not to work finding the information themselves. Another very common theme expressed by students dissatisfied with the experience was a lack of trust in the information contributed by their peers.

Departmental Response to the Improved Student Performance—

Analysis of student performance in the cooperative learning classes clearly indicated to our department the power of this educational technique, and it was judged to be inappropriate to withhold these learning tools from the traditional classes in the future simply to have a valid control group and unethical not to immediately attempt to implement some of these learning modalities in the traditional lecture-based biochemistry classes. However, the department decided that the implementation of the small group cooperative learning approach as described in this article would be so instructor intensive for even a single nonmajors biochemistry class of over 100 students each semester that it could not be sustained and would have unwanted repercussions for the other departmental course offerings (in our undergraduate majors courses and in the medical and graduate school classes). For the last year we have been incorporating on-line PBL cases (similar to those used in the cooperative learning courses described here) and “virtual” small group discussions into the nonmajors lecture-based course; we hope to describe the results of this “high context” interaction administered with a “low context” technology interface in a future manuscript.

DISCUSSION

Although a limited number of studies document superior performance on standardized tests by students training in a PBL curriculum [14, 15] the majority of medical school studies evaluating student performance suggest that students' enjoy the PBL learning experience but that their performance on standardized tests does not improve and may be slightly less than that of their peers experiencing a conventional curriculum [37]. Based on these reports, when the course design reported here was first proposed we hypothesized that we would observe similar student performance in both conventional and cooperative learning courses. The results of this study, however, show a clearly enhanced performance of students in the cooperative learning course. This result was seen in both semesters in which the course was offered. The reasons for the improved student performance are undoubtedly multifactorial.

One possibility to explain the improved student performance could be the fact that all tutorial groups were standardized by training the tutors (EAs) in weekly meetings. Another was the rigorous adherence to what could be described by Barrows as an “authentic problem-based learning environment” [3]. Whereas the authors believe that an authentic PBL environment is an extremely important curricular characteristic, identifying that environment is far more problematic. Clearly, future studies comparing student performance in different learning environments will need to define the nature of the learning experience more fully than simply using the acronym PBL. It is suggested that a well defined lexicon describing different learning environments be identified and used consistently when describing curricula.

Another explanation for the improved student performance in the cooperative learning classroom could be due to the students self-selecting such a course because it more appropriately fit their unique learning style. We do not accept this as an explanation because: 1) the first semester the course was offered students really did not know until the first day of class the full impact of the instructional method, 2) student demographics (gender, age, major) were similar for both the cooperative learning and the conventional class, 3) student performance distribution on the exams showed a similar range in scores and a similar percentage of students failing the two types of courses, and 4) students all expressed the same initial concerns about not being able to learn in this style of classroom. Moreover, if student learning style had a major influence in the decision to enroll in the cooperative learning class, then it would be expected that for the second offering of the class, in which the pedagogical style of the course was very clear because of information exchange between students, there would be a considerably improved student performance over the first time the course was offered. This was not the case. Finally, in our experience, it is the rare student who has carefully evaluated his or her learning style and then used that analysis to select courses.

Yet another possibility to explain these data is investigator bias. This possibility is always present and difficult to control. To address this possibility, one of the authors (S. M.) was a reviewer from outside the department, chosen because of his recognized expertise in PBL pedagogy. He independently evaluated the curriculum and performance of the students and EAs. Moreover, exams used in all classes were derived from a common database of biochemistry questions that contain both recall of facts and problem-solving type questions, and the tests were balanced to reflect similar discipline content and question format. In the authors' opinion, the best argument that investigator bias had little effect was that we expected to find no differences between the groups, based upon the literature, and were surprised with our data that contradicted other studies. Similarly, we do not believe that the students modified their behavior in the cooperative learning classes because they were aware that they were being evaluated; they had no reason to believe that they were being assessed in any way other than through their exam performance, and they were just trying to achieve their best possible grade to pass, graduate, or get into professional or graduate school.

Another possibility to explain the improved student performance is related to the loss of student anonymity in the small group. When a student was not prepared for class, this fact was obvious to the faculty observer, the EAs, the other students, and to the ill prepared student himself. Clearly, peer pressure is a motivating force and was present in the cooperative learning groups described in this report. However, that same pressure should be similar in all small group learning environments, and therefore it cannot by itself explain the improved performance of students in the cooperative learning classes of this report.

The authors believe that the reasons for the improved student performance in the cooperative learning classes are centered in two different areas. The first has to do with the use of peer tutors. These EAs were role models for the students in the small groups and demonstrated that it was possible to master the material. A second and we believe more significant explanation for the improved student performance stems from the conscientious development and application of a multicontextual learning environment throughout the cooperative learning classes [1]. In his monograph, Ibarra clearly defined the behavioral and learning characteristics for individuals with both low context and high context learning styles. In the design of this course, students representing each learning type were forced to encounter, understand, and explain biochemistry in both low and high context styles. This explanation, although unproven, provides an interesting challenge for future study and course design.

In conclusion, we determined that a PBL case-based small group cooperative learning approach to undergraduate biochemistry education can be a more effective educational tool for engaging students in the course material while also improving student performance. This conclusion is in contrast to much of the literature demonstrating that use of PBL case tutorials does not result in improved student performance on standardized tests. The reasons for the improved performance by students in this report are unclear but may relate to the use of our EAs, who acted as role models, or to the purposeful implementation of a multicontextual learning environment in the cooperative learning classes. These possibilities are under continued investigation.

Figure FIGURE 1..

Distribution of student final scores in introductory biochemistry classes. The square (▪) and dashed line indicate the distribution of student final grades obtained for four traditional biochemistry classes (n = 381 students). The circle (•) and solid line indicate the distribution of student scores in the two cooperative learning biochemistry classes (n = 39 students). (Final scores were determined from a student's three best exams and a final exam). The final average score for the traditional and cooperative learning classes was 73 and 77%, respectively (significantly different at p < 0.05).

Table Table I. The seven learning principles [10]
1.Learning with understanding is facilitated when new and existing knowledge is structured around the major concepts and principles of the discipline.
Educational assistants were charged with applying these principles in the interactions with their students in the cooperative learning small groups.
2.Learners use what they already know to construct new understandings.
3.Learning is facilitated through the use of metacognitive strategies that identify, monitor, and regulate cognitive processes.
4.Learners have different strategies, approaches, patterns of abilities, and styles that are a function of the interaction between their heredity and their prior experiences.
5.Learners' motivation to learn and sense of self affect what is learned, how much is learned, and how much effort will be put into the learning process.
6.The practices and activities in which people engage while learning shape what is learned.
7.Learning is enhanced through socially supported interactions.
Table Table II. Curricular comparison
Conventional content
The content of the conventional curriculum (left column) was used to design the cooperative learning curriculum (right two columns). Cases in the cooperative learning curriculum are listed by case name. The sequence of topics has been slightly altered to aid in reading the table.
 Case/LectureContent
WaterCase: pH Problem SetWater
Properties and Structure of Biological MoleculesCase: Mystery PowderProperties and Structure of Biological Molecules
Membrane Structure and TransportLectureMembrane Structure and Transport
Structure of ProteinsCase: John TannerStructure of Proteins
Analysis of Proteins Analysis of Proteins
Hemoglobin: Example of an Allosteric Protein Hemoglobin: Example of an Allosteric Protein
Thermodynamic Concepts and CatalysisLectureHow Enzymes Catalyze Reactions
Enzyme KineticsCase: CSI AlbuquerqueEnzyme Kinetics
Regulation of Enzyme ActivityLectureRegulation of Enzyme Activity
Signal TransductionLectureSignal Transduction
Energetics and MetabolismCase: Weekend AthleteEnergetics and Metabolism
Sugars and the Reactions of Glycolysis Sugars and the Reactions of Glycolysis
Regulation of Glycolysis Regulation of Glycolysis
Citric Acid Cycle Citric Acid Cycle
Glyoxylate Cycle and Regulation of CAC Glyoxylate Cycle and Regulation of CAC
Oxidative PhosphorylationCase: Diet PillOxidative Phosphorylation
Glycogen MetabolismLectureGlycogen Metabolism
HMP ShuntCase: Gerhard PrillHMP Shunt
GluconeogenesisLectureGluconeogenesis
Fatty Acid OxidationCase: Defective FormulaFatty Acid Oxidation
Fatty Acid Synthesis Fatty Acid Synthesis
Amino Acid Catabolism: NitrogenCase: JulieAmino Acid Catabolism: Nitrogen
Amino Acid Catabolism: Carbon Amino Acid Catabolism: Carbon
Complex Lipids/CholesterolLectureComplex Lipids/Cholesterol
Amino Acid SynthesisLectureAmino Acid Synthesis
Nucleotides ICase: Pain in the FootNucleotides I
Nucleotides II Nucleotides II
DNA Structure and Synthesis ICase: Designer WeedDNA Structure and Synthesis
DNA Structure and Synthesis II DNA Structure and Synthesis II
RNA Structure and SynthesisCase: Subtilisin ProblemRNA Structure and Synthesis
Genetic Code and tRNA Genetic Code and tRNA
Protein Synthesis I Protein Synthesis I
Protein Synthesis II Protein Synthesis II
Gene Regulation ICase: Changing the Food SupplyGene Regulation I
Table Table III. Comparison of student performance on quarterly tests
Average scoreTest 1Test 2Test 3Test 4
The table lists the average score, and range of scores, on the four tests in four traditional classes and two cooperative learning classes. The traditional classes took place during the same academic years as the cooperative learning classes.
Traditional class77 ± 567 ± 365 ± 768 ± 3
    (n = 4 classes)    
    (381 students)    
Cooperative learning class80 ± 275.5 ± 0.575 ± 273 ± 2
    (n = 2 classes)    
    (39 students)    
Table Table IV. Student and faculty performance on a critical thinking problem
 Conventional class studentsBiochemistry majorsFacultyCooperative learning class students
Percent of group passing question246510067
Time following teaching1 month>12 months?1 month
n>20060417

Footnotes

  1. 1

    The abbreviations used are: PBL, problem-based learning; EA, educational assistant.

Ancillary