COMPUTER-SUPPORTED COLLABORATIVE LEARNING AS A PREDICTOR OF SELF-EFFICACY AND EPISTEMIC EMOTIONS IN HIGHER EDUCATION STUDENTS IN MEXICO

Paula L. ARIAS (1), Diego-Oswaldo CAMACHO-VEGA (2), Yessica MARTÍNEZ (3), María G. DELGADILLO (4), Salvador PONCE (5), Salvador TREJO (6)
Keywords: computer-supported collaborative learning, self-efficacy, epistemic emotions, higher education students.

DOI: https://doi.org/10.26758/14.1.4

(1), (2), (4), (6) Facultad de Medicina y Psicología, Universidad Autónoma de Baja California; e-mail: (1) paula.arias@uabc.edu.mx (2) camacho.diego20@uabc.edu.mx (4) lupitadelgadillo@uabc.edu.mx (6) strejo@uabc.edu.mx
(3), (5) Facultad de Pedagogía e Innovación Educativa, Universidad Autónoma de Baja California; e-mail: (3) yessicams@uabc.edu.mx (5) ponce@uabc.edu.mx

Address correspondence to: Diego-Oswaldo Camacho-Vega, Faculty of Medicine and Psychology, Calzada Universidad 14418, UABC, Parque Internacional Industrial Tijuana, 22390
Tijuana, B.C. E-mail: (2) diego.camacho@uabc.edu.mx

Abstract

Objectives. This study investigated the predictive effect of computer-supported collaborative learning (CSCL) on self-efficacy and epistemic emotions in college students.

Material and methods. A quantitative randomized experimental design was used with 191 Mexican university students from the Psychology degree program at the Autonomous University of Baja California. Participants were randomly assigned to either a collaborative group or a non-collaborative group. Both groups completed the Online Learning Self-Efficacy Scale and the Epistemic Emotions Scales before and after solving the Cognitive Reflection Test.

Results. The results showed that the collaborative group reported significantly higher levels of surprise, confusion and anxiety after solving the Cognitive Reflection Test, but lower levels of curiosity. The non-collaborative group showed significant differences in surprise, confusion, and frustration. Comparing both groups in the posttest, the collaborative group showed higher levels of excitement and lower levels of boredom. The regression analysis showed that CSCL does not predict self-efficacy, but it does predict epistemic emotions, particularly anxiety and boredom.

Conclusions. The findings suggest that CSCL can be a valuable tool for fostering positive epistemic emotions in college students, such as curiosity and excitement. However, more research is needed to understand the relationship between CSCL and self-efficacy, as well as the role of negative epistemic emotions in collaborative learning.

 Keywords: Computer-supported Collaborative Learning, Self-efficacy, Epistemic Emotions, Higher Education Students.

 Introduction

 The COVID-19 pandemic that started in China in 2019 unleashed transformations in multiple social spheres at the global level. The consequences of the pandemic were strongly felt in health systems, leading to the restriction and closure of economic activities, political changes, modification of social behavior patterns, and a radical transformation in educational activity at all levels worldwide, including higher education, which had no benchmarks or previous experience in these conditions (Aristovnik, Keržič, Ravšelj, Tomaževič, & Umek, 2021). There were some exceptions, such as the suspension of educational services caused by the AH1N1 influenza virus during 2009, as well as emergencies due to armed and migratory conflicts in African and Middle Eastern countries (Zambrano-Ponce & Garcia-Espinosa, 2022).

The transformations the pandemic caused in higher education students went beyond academics to their physical and mental balance (Keržič et al., 2021). In terms of academics, educational institutions transferred their face-to-face courses to the online modality at an accelerated pace, turning online learning into a mandatory teaching and learning process (Aristovnik et al., 2021). However, due to the haste of this transition, certain skills required of students, in particular, the self-regulated learning skills needed for the online courses, were not adequately addressed (Edisherashvili, Saks, Pedaste, & Leijen, 2022).

The COVID-19 pandemic not only had an emotional impact on students’ day-to-day lives, but it also made more evident the role of emotions in their learning process (Pedrosa et al., 2020).

Particularly in the learning context, epistemic emotions have played a paramount role. Epistemic emotions are emotions that arise specifically in relation to knowledge and learning. They can be positive, encouraging engagement and a deeper understanding, or negative, hindering learning and motivation. Based on their valence, the epistemic emotions can be categorized as positive or negative. Examples of positive epistemic emotions include curiosity: (a desire to learn and explore new things), enjoyment (finding learning pleasurable and engaging), surprise (experiencing something unexpected or challenging existing beliefs), confidence (feeling capable of learning and mastering new concepts), and hope (believing in one’s ability to succeed and reach learning goals). For its part, examples of negative epistemic emotions include boredom (finding learning dull and monotonous), frustration (feeling stuck or unable to grasp a concept), anxiety (feeling worried or stressed about learning and performance), confusion (feeling uncertain or not understanding a concept), and shame (feeling embarrassed or inadequate due to learning difficulties) (Pekrun, Vogl, Muis, & Sinatra, 2017). These emotions are involved in the aspects of learning related to the cognitive and epistemic qualities of information and information processing (Chevrier, Muis, Trevors, Pekrun, & Sinatra, 2019).

The COVID-19 lockdown also seems to have affected student motivation, particularly self-efficacy. Self-efficacy is a concept from social cognitive theory that refers to a person’s belief in their ability to succeed in a particular task or situation. According to Pintrich, Smith, Duncan, and Mckeachi (1991), the motivational process is made up of six basic components: (1) intrinsic goal orientation; (2) extrinsic goal orientation; (3) task value; (4) control of learning beliefs; (5) anxiety during the test application process; and (6) self-efficacy for learning and performance. Askar and Umay (2001) define self-efficacy as the belief in one’s ability to organize and execute the courses of action required to produce successfully given attainments, behaviors, or actions. Zimmerman (2000) emphasizes that self-efficacy is “a judgment of one’s capabilities to perform and succeed at a task. In summary, the element of self-efficacy alludes to the motivation, perseverance, expectations, and self-reflexivity that individuals have with respect to the goals they set for themselves (Bandura, 2012).

While it has been proposed to positively impact students’ emotions and motivation during online courses, the inclusion of collaborative activities within courses is an appropriate strategy to facilitate the achievement of educational goals, as it has been shown to positively impact students’ emotions and motivation through peer relationships (Hiltz & Wellman, 1997).  Thus, recent studies refer to the importance of learning to collaborate online, seen as a teaching-learning method that achieves greater productivity, long-term retention, better relationships among students and that promotes active learning in a fluid and student-centered manner, as well as in the skills needed to perform in daily life Recent studies have also highlighted the importance of learning to collaborate online, as this teaching-learning method can lead to greater productivity, long-term retention, better relationships among students, active learning in a fluid and student-centered manner, and the development of skills needed for daily life (Archer-Kath, Johnson, & Johnson, 1994; Dorego & Villasana, 2007; García-Chitiva & Suárez-Guerrero, 2019).

Collaborative learning is defined as the acquisition of knowledge, skills, or attitudes that occurs as a result of group interaction (Trentin, 2010). When this collaborative process is mediated by computers, it is defined as computer-supported collaborative learning (CSCL). This collaboration can take place synchronously, where participants interact in real time or asynchronously (Stahl, Law, Cress, & Ludvigsen, 2014). In CSCL, students collaborate in a coordinated manner and enrich each other to perform a task, making use of technological and virtual tools (Reyes & Quiroz, 2020). From this perspective, knowledge is not something that students receive from a teacher but is the result of a dialogue and a shared task that allows them to develop concepts, acquire techniques and skills, and strengthen the relationships they create with their peers (Coll & Colomina, 1990). However, existing virtual platforms often reproduce traditional forms and sequences of learning, i.e., activities are organized based on behaviorist methodologies and mostly individual performances: notes, readings, exams, etc. (Silva, 2017). Therefore, it is necessary to enhance the use of innovative methodologies in educational processes (Gisbert & Johnson, 2015).

Based on the above, the aim of this paper is to identify whether computer-supported collaborative learning (CSCL) predicts an increase in self-efficacy and positive epistemic emotions (e.g., surprise, curiosity and enjoyment) in college students.

The hypothesis for this work is that CSCL activities increase the level of positive epistemic emotions and self-efficacy in students compared to non-collaborative activities.

Methodology

 Design

This research is based on a quantitative method with a random assignment, experimental design.

Participants

The sample consisted of 191 Mexican university students (age mean = 21.13, 50.80% females) of the Psychology degree program at the Autonomous University of Baja California. The age range of 18 to 36 years was selected because, according to the XVII Study on the Habits of Internet Users in Mexico by the Internet Association MX (2023), the profile of the user who mostly uses the Internet is within that age range.

A total of 191 participants were randomly selected from the population. The sampling method used was probabilistic sampling. The G*Power program was used to determine the sample size, taking into account the effect size (w = 0.20), error probability (α = 0.05), and statistical power (1 – β = 0.80) as recommended by Cohen (1992).

Material and methods

 Instruments

The Epistemic Emotions Scales (EES) developed by Pekrun et al. (2017) was used. The EES is a Likert-type scale that measures the level of epistemic emotions experienced by students while performing a task. The scale ranges from 1 (not at all) to 6 (very strong) and the emotions it measures are surprise, curiosity, enjoyment, confusion, anxiety, frustration, and boredom. The instrument includes contextualized instructions. The reliability of the EES has been reported to be good to excellent, with a Cronbach’s alpha of .76 to .88 (Pekrun et al., 2017).

Likewise, the Online Learning Self-Efficacy Scale (OLSES), developed by Zimmerman and Kulikowich (2016) was used to determine the self-efficacy perceptions of university students in online learning environments. The scale consists of 19 items, distributed into three factors (learning in the online environment, time management and technology use). The reliability of the instrument has been reported to be high for the three factors (α =0.89, α = 0.85 and α = 0.84, respectively) (Zimmerman & Kulikowich, 2016).

The activity assigned in both collaborative and non-collaborative groups was the Cognitive Reflection Test (CRT) proposed by Frederick (2005). This test promotes the ability to reflect on or question the intuitive answer (the first answer that comes to mind) by presenting dilemmas that require testing mathematical, rational, and open-minded thinking The test consists of the following three questions: 1) A bat and a ball cost $1.10 total, the bat costs $1.00 more than the ball, how much does the ball cost, 2) If 5 machines take 5 minutes to make 5 widgets, how long would it take 100 machines to make 100 widgets, 3) In a lake, there’s a group of water lilies. Every day, the patch doubles in size. It takes 48 days to cover the entire lake. How long would it take to cover only half?

Procedure

After the students signed the informed consent form, they individually completed a pre-survey with questions related to sociodemographic information. Subsequently, a randomization procedure was performed to assign participants to one of two groups: collaborative group (experimental group) and non-collaborative group (control group). Within the experimental group, small subgroups of three people were randomly assigned to solve the CRT together. While students in the collaborative group communicated through a live chat on the Google Meet platform to agree while answering the CRT, those in the non-collaborative group solved the CRT individually. Next, levels of epistemic emotions were measured with the EES and levels of self-efficacy with the OLSES for both groups before and after the treatment. Finally, the data obtained were collected and analyzed using JASP 0.13.1.0 software.

Statistical Analysis

First, descriptive statistics were calculated for the sociodemographic data and for the results obtained in the EES and OLSES instruments. The non-normal distribution of the data was identified by means of the Shapiro-Wilk coefficient. Therefore, the decision was made to use non-parametric statistics.

Second, pretest and posttest results were compared in each of the groups calculating the Wilcoxon signed-rank test to identify changes in self-efficacy and epistemic emotions.

Third, a comparison between the groups was performed to identify differences in the variables through the Mann-Whitney U calculation. Finally, to identify whether CSCL predicts an increase in self-efficacy and epistemic emotions, Spearman’s correlation coefficient was first calculated to test multicollinearity and then, a multiple linear regression was performed with CSCL as the dependent variable. The data obtained were collected and analyzed using JASP 0.13.1.0 software.

Results

 Comparison by groups

The collaborative group did not show significant differences in the pretest and post-test self-efficacy report. However, the epistemic emotions of this group showed significant differences (p < .001) in terms of surprise (Mpretest = 2.34; Mposttest = 3.50), curiosity (Mpretest = 4.94; posttest = 4.24), confusion (Mpretest = 2.60; Mposttest = 3.87) and anxiety (Mpretest = 2.96; postest  = 3.47).

On the other hand, the non-collaborative group showed significant differences in the epistemic emotions of surprise (Mpretest = 2.27; Mposttest = 3.50; p<.001) and confusion (Mpretest = 2.16; Mposttest = 3.60; p < .001), as well as in frustration (Mpretest = 1.94; Mposttest = 2.59; p = .002).

Comparison between groups

As can be seen in Table 1, the results from the comparison between groups regarding the levels of self-efficacy and epistemic emotions showed that the students in the collaborative group had significantly higher levels of curiosity, confusion, and anxiety in the pretest. However, in the posttest, only excitement and anxiety maintained the significant difference, in addition to the differences in boredom.

Table 1
Descriptive statistics and between-groups comparisons (to see Table 1, please click here).

CSCL prediction on self-efficacy and epistemic emotions

To test the proposed predictive model, where the dependent variable is CSCL, a logistic regression analysis was conducted for each independent variable. The analysis indicated that collaborative learning does not predict self-efficacy. However, the analysis showed that, in general, epistemic emotions are predicted by collaborative learning, particularly by higher levels of anxiety and lower levels of boredom, between 14% and 24%, respectively (see Table 1 and Table 2).

Table 2
Logistic regression of the epistemic emotions model with the dependent variable (to see Table 2, please click here).

Discussions

The hypothesis of this study was that computer-mediated collaborative activities would increase the level of positive epistemic emotions. This hypothesis was partially supported, as computer-mediated collaborative work was found to predict a change in epistemic emotions, but from a perspective focused on negative emotions. The present study was unable to validate the hypothesis of the role of computer-mediated collaborative work in relation to self-efficacy.

The underlying hypothesis of this research is that student social and emotional presence fosters socio-cognitive processes of negotiation, which in turn enhance individual learning outcomes. This is especially true of collaborative learning, especially computer-supported cooperative learning (CSCL). This can even improve their levels of self-perceived satisfaction (Hernández-Sellés, 2021).

Within this context, the role of the student is substantially modified as they are encouraged to be more autonomous, reflective, and dynamic. Additionally, students empowered to take charge of their own education and that of their peers (Cotán., García, & Gallardo, 2021).

The findings of this study showed that significant differences were obtained in epistemic emotions, but not in the levels of self-efficacy, which is consistent with other research that has found that a high percentage of students have low academic self-efficacy (Suria-Martínez, 2023; Bonilla-Yucailla, Balseca-Acosta, Cárdenas-Pérez, & Moya-Ramírez, 2022). This is a concern for the school system, as self-efficacy is recognized as a valuable tool for enhancing other capabilities needed by the student in the academic context. Similarly, several studies have found a positive association between self-efficacy and school performance and motivation, commitment and expectations, university access, self-regulation of activities, positive affect, and personality (Álvarez-Pérez, López-Aguilar, & Garcés-Delgado, 2021; González-Benito, López-Martín, Expósito-Casas, & Moreno-González, 2021; Rodríguez, Figueroa-Varela, & Muñoz Salazar, 2023; Yupanqui-Lorenzo, Mollinedo, & Montealegre 2021).

Regarding positive epistemic emotions, our results showed higher levels of curiosity and excitement in the collaborative group. This is in line with the empirical evidence of other authors, who argue that students who frequently experience positive emotions linked to their studies will have available within their repertoire of personal resources those of psychological capital, such as self-efficacy, hope, optimism, and resilience (Carmona-Halty, Villegas-Robertson, & Marín-Gutiérrez, 2019).

Coordinating the cooperative learning activities of individuals can be challenging, particularly when technology is being used to facilitate the meeting. In higher education, the main challenges to be solved are the acceptance of virtual collaborative mediation and the need to implement a combination of pedagogical strategies and virtual tools that guarantee the achievement of disciplinary competencies (García-Chitiva & Suárez-Guerrero, 2019).

Even though the CRT task is considered a single cognitive activity, its presentation across three questions suggests that evaluating epistemic emotions for each question individually may be necessary.

In view of the above, this research has the merit of having carried out a comparative study among groups of university students who solve academic problems using computerized collaborative learning. It has demonstrated that epistemic emotions are relevant during the collaborative process and, on the other hand, it shows that self-efficacy requires further studies to understand its associated variables, particularly in relation to virtual learning environments.

Conclusions

 In conclusion, Computer-supported Collaborative Learning can have a positive impact on students’ epistemic emotions, such as curiosity and excitement. However, the findings of this study suggest that CSCL may not be effective in increasing self-efficacy, but further research is needed. This study also highlights the challenges of coordinating collaborative activities in virtual learning environments. The application of unconventional strategies, such as virtual collaborative tasks, and the requirement to implement a combination of pedagogical strategies, which ensure the achievement of disciplinary competencies, present the biggest challenges in higher education.

Finally, according to our results, educators should. monitor the negative emotions of boredom and anxiety and their effects on students’ self-efficacy, as well as encourage students to develop positive emotions like curiosity and self-efficacy beliefs by providing them with opportunities to succeed.

Acknowledgements

 A summary of this paper was presented at the online international conference: Individual, family, society – contemporary challenges, fifth edition, 4 to 5 October 2023, Bucharest, Romania, and published in the journal Studii şi Cercetări de Antropologie, No. 8/2023.

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