Abstract
The authors of this study utilized the logistic regression analysis using extreme student groups (top and bottom quartiles) defined by students' collaborative learning scores to develop a model for predicting group membership of low and high levels of collaborative learning college students. The focus of the study was to identify characteristics of the learning environment that differentiate between high and low collaborative learning groups. Results of the logistic regression showed a statistically significant model that can be used to reliably predict student's classification into low or high collaborative learning groups based on the selected institution and personal variables. The logistic regression model showed the lowest total percent correctly classified was at 98.1% while the highest total percent correctly classified was at 98.6%. Majority of the model variables made significant differences between the low and high collaborative learning groups. ANOVA results indicate significant group differences in all the predictor variables.
TopIntroduction
The world is experiencing a situation that has never been experienced in recent history due to the current Corona Virus (COVID-19) pandemic. Institutions of learning have been forced to device instructional formats that observe both the medical and government guidelines for limiting the spread of COVID-19 while at the same time ensuring that teaching and learning goes one. Different institutions are trying different instructional delivery methods and terms such as synchronous, asynchronous, hybrid, distance education, on-campus, off-campus, in-person have continued to dominate discussions in different institutions. This study looks at one form of teaching and learning that cuts across all forms of instructional delivery systems.
In collaborative learning, the instructor’s role is to organize the groups and learning activities but then let the groups “assume the responsibility for learning” (Foote, 2001, p. 2). Collaborative learning is more than students working on group projects and according to Foote, successful facilitation of collaborative learning contains “clear interdependence among students, regular group self-evaluation, interpersonal behaviors that promote each member’s learning and success, individual accountability and personal responsibility and the frequent use of appropriate interpersonal and small group social skills” (Foote, 2001, p. 2). Baker and Campbell (2005) reported about students from a mathematics course who were placed into random groups and asked to develop mathematical proofs in response to difficult problems they were given. The researchers discovered that each group member played an important role in the learning of other members. One especially interesting observation was that students who didn’t know the material as well as others but kept the group focused and did not allow it to quit when it faced roadblocks were just as valuable to the group as those who knew the material well. On the other hand, they noted that the most confident student not being as knowledgeable as the other students can cause issues within the group (Baker & Campbell, 2005). Sibbernsen (2014) studied the impact of placing students in groups versus allowing them to work individually when applying a specific curriculum to an astronomy course. The authors discovered that although placing the students in groups had little quantitative impact on student performance, those students who were placed in groups were more likely to take on more challenging problems than those who worked individually (Sibbernsen, 2014). Based on this research, students’ confidence grows as they work with their peers. Higher levels of confidence can lead to higher levels of engagement and success.
In addition to collaborative learning, a student’s relationship with his or her instructor is also a contributing factor to engagement in the classroom. Contact with faculty members can include both class-oriented and non-class-oriented interactions. Non-class-oriented interactions might include students talking with faculty members about future academic or career plans, which shifts the relationship of the faculty member from an instructor to a mentor (Kuh, 2003). Christophel (1990) observed teacher immediacy behaviors - those behaviors that make others feel welcome and comfortable in the classroom - and their impact on student motivation and learning. Christophel determined these types of behaviors positively correlated with both student motivation and learning, suggesting the relationship between a teacher and student influences the student’s academic performance.
Engagement in the classroom early in an academic career plays an especially important role in student success (McClenney & Arnsparger, 2012). Engagement in the classroom can come in many forms, including working with other students and developing a relationship with an instructor. A student’s engagement in the classroom and in the campus community can impact the student’s academic performance. Tucker (1999) observed that students who do not have a sense of belonging in their academic community are constantly aware of their isolation and this often leads to poor academic performance or attrition.
Key Terms in this Chapter
Collaborative Learning Strategies: Activities in which the students are actively involved or engaged or are required to take an initiative in enhancing their own learning. Active learning strategies include how often the student worked with other students, student knowing other students in class, student explaining his/her ideas to other students, student learning from other students, student cooperating with other students on class activities, working in groups in class, and being involved in other vigorous action (individual/joint) in pursuit of knowledge or skills (Chemosit, 2004).
Student-Faculty Interaction: The contact between the faculty and the student. This includes course related activities and activities other than the course work/outside the course work (Chemosit, 2004). The measure that describes student-faculty interaction includes activities such as teacher taking a personal interest in student, teacher considering student’s feelings, teacher helping the student when he/she is trouble with the work, and teacher talking to with the student.
In-Person: An instructional format where no more than a certain percent, e.g., 75% of the course instruction may be delivered via electronic communication or equivalent mechanisms.
Logistic Regression: This is a kind of regression analysis often used when the outcome variable is dichotomous and scored 0, 1. Logistic regression is also known as logit regression and when the dependent variable has more than two categories it is called multinomial. Logistic regression is used when predicting whether an event will happen or not.
Odds: Odds in logistic regression and Rasch measurement modeling refers to the probability of belong to a group (present) divided by the probability of not belonging to that group (not present). The formula for computing odds is given as (P/(1-P)), where P is the probability of an event occurring, that is, an outcome being 1. 1-P is the probability of an event not occurring (of the event being a 0).
Odds Ratio: This is one of the important results in logistic regression. This is what must be computed to allow researchers to answer their research questions. The research question could be to determine whether there is a group (participating in a program or not) difference in college retention.
Outliers: One of the data preparation techniques for checking whether there are data points that could have undue influence on the results of the study is to check for outliers in the dataset. An outlier is technically a data point outside of your distribution; so potentially influential because may have undo effect on distribution.
Peer Learning and Motivation: Motivation has been defined as the energy that is innate within all individuals, and high levels directed toward a situation results in greater amounts of energy expended on that task. The greater desire and higher levels of energy targeted at accomplishing a goal the higher the levels of performance (McDevitt & Ormrod, 2004). Operationally, the terms “peer learning and motivation” and “motivation involvement” will be considered equivalent. This includes encouragement for students to express their own ideas, encouragement for students to participate in discussions, the extent to which students are encouraged to compare ideas, the extent to which students are involved in discussions among themselves, and the extent to which students learn from each other.
Hybrid: This is where a certain percent, e.g., 75% or higher 75-99% of instruction is delivered via electronic communication or equivalent mechanism, that includes a face-to-face component.
Distance Education: A distance education is instructional delivery method where the interaction between the students and the instructor is done synchronously or asynchronously, that is the instructor and the learner are physically separated. A distance education course is one in which 51% or more of the instruction and interaction occurs via electronic communication or equivalent mechanisms with the faculty and students physically separated from each other.