METACOGNITIVE SKILLS, SELF-REGULATED LEARNING, AND ACADEMIC PERFORMANCE AMONG FIRST-YEAR UNDERGRADUATE STUDENTS AT FELIX HOUPHOUET BOIGNY UNIVERSITY IN ABIDJAN

Revue Internationale de la Recherche Scientifique (Revue-IRS) ISSN: 2958-8413 Vol. 3, No. 6, Novembre 2025 This is an open access article under the CC BY-NC-ND license. http://www.revue-irs.com 6702 METACOGNITIVE SKILLS, SELF-REGULATED LEARNING, AND ACADEMIC PERFORMANCE AMONG FIRST-YEAR UNDERGRADUATE STUDENTS AT FELIX HOUPHOUET BOIGNY UNIVERSITY IN ABIDJAN Aya Michèle Edith Koffi, Département de Psychologie, Université Félix Houphouët Boigny d’AbidjanCôte d’Ivoire Abstract: This study aims to understand the influence of metacognitive skills and self-regulated learning on the academic performance of first-year university students. With this in mind, a sample of 140 first-year undergraduate students was selected using cluster sampling at Félix Houphouët Boigny University in Abidjan (Ivory Coast). Two questionnaires relating to the different variables were administered to them. After the data were analyzed, the means obtained were compared using Student's t-test for independent samples in SPSS software. The results showed, first, that first-year undergraduate students who use metacognitive skills in their learning process have higher academic performance than their peers who do not use metacognitive skills in their learning process. Second, undergraduate students who apply self-regulated learning in their learning process perform better academically than their peers who do not apply self-regulated learning in their learning process. Keywords: Self-regulated learning, undergraduate students, metacognitive skills, academic performance. Revue Internationale de la Recherche Scientifique (Revue-IRS) - ISSN : 2958-8413 http://www.revue-irs.com 6703 Résumé: Cette étude vise à comprendre l’influence des habilités métacognitives et de l’apprentissage autorégulé sur la performance académique des étudiants de première année d’université. Dans cette optique, un échantillon de 140 étudiants de licence 1 a été sélectionné par la technique d’échantillonnage par grappe à l’Université Félix Houphouët Boigny d’Abidjan (Côte d’Ivoire). Deux questionnaires relatifs aux différentes variables, leur ont été administrés. Après le dépouillement des données, les moyennes obtenues ont été comparées avec le t de Student pour échantillon indépendant dans le logiciel Spss. Les résultats ont montré premièrement, que les étudiants de licence 1 qui impliquent des habiletés métacognitives dans leur processus d’apprentissage ont une performance académique supérieure à celles de leurs pairs qui n’impliquent pas d’habiletés métacognitives dans leur processus d’apprentissage. Deuxièmement, que les étudiants de licence 1 qui mettent en application l’apprentissage autorégulé dans leur processus d’apprentissage ont une performance académique supérieure à celle de leurs pairs qui ne mettent pas en application l’apprentissage autorégulé dans leur processus d’apprentissage. Mots clés : Apprentissage autorégulé, étudiants de licence 1, habilités métacognitives, performance académiques. Digital Object Identifier (DOI): https://doi.org/10.5281/zenodo.17687896 1 Introduction Academic performance is today, the objective pursued by all the universities in the world. This is measured through the results produced each year by the students. However, the prevailing observation is the high rate of failure and dropout in these universities. In particular, among first-year undergraduate students. J-P. Vandamme et al (2006: 40) explain that : « In French-speaking universities in Belgium, 60% of first-generation students fail or drop out in the first year ». According to J-L. Dupont (2003: 39) : For the year 2002-2003, 46.2% of students who entered in 2001-2002 in the first year of undergraduate studies (including IUT and university engineering courses) were admitted in 2nd year, 29% repeated their first year and 24.8% left the university system, Revue Internationale de la Recherche Scientifique (Revue-IRS) - ISSN : 2958-8413 http://www.revue-irs.com 6704 permanently, temporarily or with a view to an orientation towards higher non-university courses (STS, paramedical and social training). Thus, R.Bodin andM. Millet (2011 : 65) indicate that : The first university cycles are characterized by a particularly high evaporation rate in the first year, compared to other possible courses in hig her education. Each year, 25% of students enrolled in the first year of bachelor's degree do not re-enroll the following year. Concerning first-year psychology students at Félix Houphouët Boigny University in Abidjan, « from 2013 to 2016 the rate of students who failed increased from 10% to 25% in the number of major teaching units » (K. A. Kouadio et al, 2024: 6). In view of this alarming data indicating the problem of academic performance at the level of undergraduate students, it appears more than necessary to look into this phenomenon. Because anyone who enrolls in university for post-secondary studies must be able to continue their studies and graduate with a degree. This is where the term academic performance takes on its full meaning. M. A. Deniger (2004: 3) defines academic performance as « the achievement of learning objectives related to the mastery of knowledge specific to each stage of the school path taken by the studentand ultimately obtaining a diploma or integration into the job market ». All students must therefore be able to master the learning related to their specialties and their levels at each stage of their course. This allows them to obtain their various end-of-cycle diplomas and to enter the professional world. However, the observation made is that they have difficulty getting through the first year of university. Thus, this difficulty, experienced by the students of the bachelor's degree 1, has aroused our interest in this research. Several studies have already been undertaken on academic performance and the factors likely to influence it. P. Saeed (2010 : 6) conducted, Research on the quality of learning and the academic performance of students. From the results, it appears that the student's perception of the university environment influences the meaning given to his act of learning. When the university environment is perceived as interesting, stimulating and relevant, the student is more mobilized for better learning, a richer more open educational relationship and a more important intellectual complicity with the teacher. So it is the quality of the tools and methods used in the work environment, which arouse in students the desire to learn. Academic performance Revue Internationale de la Recherche Scientifique (Revue-IRS) - ISSN : 2958-8413 http://www.revue-irs.com 6705 is then a function of the perception that students have of their work environment and the opportunities offered by this environment. However, while beingin a rich environment, students to be successful must become aware of their learning and engage in achieving the set objectives. G.Benoit-Chabot and P. L. Denis (2018: 129), indicate as a result that : The only preference for active experimentation moderates the relationship between the conscientiousness factor and academic performance. For them, conscientious students obtain the best results on the final exam when they have a preference for learning through active experimentation. Then, the integration of pedagogical methods that can promote learning through active experimentation (practical work, internships, stimulation work and experimentation work) is a contribution to improving academic performance among these students. All these studies have explored the academic performance of first-year university students and the factors likely to influence it. However, none of them mentioned the effect of metacognition and self-regulated learning on this performance. However, students really understand and take ownership of the content of learning, when they use their metacognitive skills to successfully complete learning tasks. According to R. C. Pianta et al (2008: 6), « the development of metacognitive skills and understanding of one's own thought processes play a crucial role in the child's progress ». Thus, these elements are put in place at the level of the learners, through an internal organization and a well-defined structuring of the tasks to be performed. Students mobilize problem-solving strategies based on the knowledge they have and the methods they use to obtain satisfactory results. In this way, they engage in the pursuit and achievement of set performance goals. This approach involves self-regulated learning. B. J. Zimmerman and D. H. Schunk (2011: 1) define selfregulated learning as « processes through which learners activate and sustain their cognitions, emotions, and behaviors that are systematically directed toward the achievement of a personal goal ». Therefore, it is not only about using metacognitive skills, but the student must be able to regulate them and direct them with motivation towards the achievement of an expected performance goal. Metacognitive skills and self-regulated learning therefore appear as variables that can influence the academic performance of first-year university students. Thus, the concern that legitimizes this study is to know howthe involvement ofmeta-cognitive skills and the application of self-regulated learning in the learning process, can influence this academic performance? The general objective of this study therefore aims to understand the Revue Internationale de la Recherche Scientifique (Revue-IRS) - ISSN : 2958-8413 http://www.revue-irs.com 6706 influence of metacognitive skills and of self-regulated learning on academic performance among first-year undergraduate students. In order to achieve this objective, we put forward the following hypotheses: H1: first-year undergraduate students who involve metacognitive skills in their learning process have a higher academic performance than their peers who do not involve metacognitive skills in their learning process. H2: First-year undergraduate students who apply self-regulated learning in their learning process have a higher academic performance than their peers who do not apply self-regulated learning in their learning process. To establish the veracity of our hypotheses, our study will be based on the research methodology, the results and their discussion. 2 Research methodology The methodology section allows us to describe and analyze our different variables, to indicate the sampling technique used for the selection of the sample, the data collection tools and the statistical processing of these data. 2.1 Description and analysis of variables The first independent variable is metacognitive ability. According to L. Lafortune et al (2000: 12-13): a metacognitive skill is the ability to mobilize one's knowledge and know-how, with the explicit intention of planning the execution of a task, in order to better supervise, evaluate it, and make a critical judgment on the effectiveness of one's approach with regard to the strategies put in place and the goal pursued. This judgment not only enriches one's metacognitive knowledge, but also develops a conscious knowledge that can be deployed in increasingly complex situations. The main manifestations of a metacognitive skill are the control and regulation of the learning process because they are the result of a constant and conscious evaluation and thus promote reuse. This makes it possible to put in place adapted metacognitive strategies, to be more effective during learning. In this work, we define metacognitive skills as the actions and strategies developed by students to precisely select, use, control and regulate information adapted to a problem situation to be resolved. It is a qualitative variable. These modalities are the students Revue Internationale de la Recherche Scientifique (Revue-IRS) - ISSN : 2958-8413 http://www.revue-irs.com 6707 who involve metacognitive skills in their learning process. These deploy a set of strategies to effectively integrate, understand, regulate and restore their different learning. On the other hand, students who do not involve metacognitive skills in their learning process stick to notetaking, rote learning and the accumulation of knowledge. The second independent variable is self-regulated learning. For D. H. Schunk and P. A. Ertmer (2012: 644), « self-regulated learning refers to all the processes by which subjects activate and maintain cognitions, affects and behaviors systematically oriented towards achieving the goal ». B. J. Zimmerman (1989: 329) specifies that « learners are self-regulated when they actively participate in their own learning process from a metacognitive, motivational and behavioral point of view ». Self-regulated learning therefore refers in this article to the ability to put in place metacognitive strategies, while having the motivation to regulate them and direct them towards the achievement of a fixed performance objective. This variable is qualitative. These modalities are students who apply self-regulated learning in their learning process. The latter use metacognitive strategies, depending on the learning tasks to be carried out, engage with motivation in the production of self-regulated intellectual work, while taking into account the management of time and materials. Students who do not apply self-regulated learning in their learning process limit themselves to returning the knowledge learned by heart and no longer have resources when they forget part of their knowledge. The dependent variable is academic performance. Referring to M. A. Deniger (2004: 3), « academic performance corresponds to the level of mastery of knowledge specific to each stage of the school career of the learner. It is crowned by obtaining a diploma or integration into the job market ». It is a quantitative variable. It is measured from the average obtained by students in the first session. 2.2 Sampling method In our research, we need license 1 students from the Félix Houphouët Boigny University of Abidjan, who follow the same teaching programs and who have the same evaluations. So, to constitute a sample adapted to our study, we will use the cluster sampling method. According to S. Beavogui (2012: 9), This method involves dividing the population into groups or clusters. Then, one or more clusters are randomly selected to represent the total population. The sample then consists of the units within the cluster or clusters selected. The purpose of this type of Revue Internationale de la Recherche Scientifique (Revue-IRS) - ISSN : 2958-8413 http://www.revue-irs.com 6708 sampling is to reduce costs by creating pockets of individuals instead of extending the sample over the entire territory. Our sample therefore consists of 140 first-year undergraduate students from the Psychology Department of Félix Houphouët Boigny University for the year 2024-2025. 2.3 Data collection tools Our data collection instruments are questionnaires. The measurement of metacognitive skills in the learning process will be carried out with the Metacognitive Awareness Inventory (MAI) by G. P. Schraw and R. S. Dennison (1994: 472-475), This questionnaire is composed of two main parts. Each of the dimensions included in the two parts contains items. The first focuses on knowledge about cognition and includes three dimensions. We have declarative knowledge (8 items), procedural knowledge (4 items) and conditional knowledge (5 items). The second part focuses on the regulation of cognition and has five dimensions. These are planning (7 items), information management strategies (10 items), monitoring comprehension (7 items), debugging strategies to correct errors (5 items) and evaluation (6 items). The first part consists of 17 items and the second part of 35 items, with the possibility of answering, true or false and for each answer, scores of 1 for true and 0 for false are assigned. The questionnaire to be sent to students does not contain the dimensions and parts mentioned. It is only composed of items which are around 52 in number. To measure the implementation of self-regulated learning in the learning process of first-year students, we will use the French translation of the questionnaire by L. Barnard et al (2009: 36), the Online Self-Regulated Learning Questionnaire (OSLQ). This questionnaire was developed by these authors to measure the self-regulation of student learning during online courses. It is composed of 6 sub-scales, namely goal setting (5 items), environment structuring (4 items), task strategies (4 items), time management (3 items), help-seeking (4 items) and self-assessment (4 items). This gives a total of 24 items. The possible answers and the scores assigned range from strongly agree (5) to strongly disagree (1). We have adapted this tool to our study, to measure the self-regulation of learning during faceto-face courses. For this purpose, some items have been modified. Then, we carried out a presurvey on a sample of 20 participants. With the data collected, we carried out the tests of the normal law, factor analysis and Cronbach's alpha in the Spss software, to verify the reliability Revue Internationale de la Recherche Scientifique (Revue-IRS) - ISSN : 2958-8413 http://www.revue-irs.com 6709 of our tool. The results of the law normal allowed us to remove items 1, 5, 11 and 20. The factor analysis allowed us to retain 3 dimensions which take into account 11 items, namely items 3,6,9,10,13,14,16,18,19,21 and 23. These are numbered from 1 to 11 in the new scale. The Cronbach's alpha obtained is equal to .870. The new instrument is reliable and includes 11 items. The header of these various questionnaires administered to students is marked with the student's name and first names, as well as instructions inherent to the completion. 2.4 Administration of data collection material The questionnaires were completed in the tutorial room. We received the students in groups of 35 and gave them the questionnaires which they completed, indicating their names and first names. The instructions given for each questionnaire are to tick the box of the items that best correspond to their choice of answer. We also explained to the students that we need information on their different working methods and that the answers are individual and personal. We also guaranteed the anonymity of their answers. Each of the groups proceeded to complete the first questionnaire, then the second. At the end of the exercise, we made sure that the questionnaires were filled out properly and collected them. The different group sessions lasted 7 to 10 minutes for completing the two questionnaires. 2.5 Data analysis The purpose of using these questionnaires is to have comparable groups within our sample. Thus, the analysis was done by completed questionnaire. For each subject, the scores were added up to find the total obtained. Regarding the questionnaire measuring metacognitive abilities, when first-year undergraduate students have a score lower than 26, they do not involve metacognitive abilities in their learning process. However, when they have a score greater than or equal to 26, they involve metacognitive abilities in their learning process. As for the questionnaire on self-regulated learning, first-year undergraduate students who obtain a score lower than 28 do not apply self-regulated learning in their learning process. On the other hand, those who have a score greater than or equal to 28 apply self-regulated learning in their learning process. Therefore, after the data analysis and based on the scores obtained by the students, our sample is composed of 78 students who involve metacognitive abilities in their learning process and 62 students who do not involve metacognitive abilities in their Revue Internationale de la Recherche Scientifique (Revue-IRS) - ISSN : 2958-8413 http://www.revue-irs.com 6710 learning process; 75 students who apply self-regulated learning in their learning process and 65 students who do not apply self-regulated learning in their learning process. 2.6 Statistical data processing The statistical data processing consists of comparing the averages of academic performance obtained by these first-year undergraduate students in the first exam session between these different groups. This comparison is performed using Student's t-test for independent samples in the Spss software. The results will allow us to either confirm or disprove our hypotheses. 3 Study results 3.1 Result of hypothesis 1 Table I: Results of the comparison of academic performance averages between first-year undergraduate students who involve metacognitive skills in their learning process and first-year undergraduate students who do not involve metacognitive skills in their learning process Group Statistics Metacognitive skills N Mean Standard deviation Student' s t-test Df Academic performance First-year undergraduate students who involve metacognitive skills in their learning process 78 14,4147 ,58559 13,657 138 First-year undergraduate students who do not involve metacognitive skills in their learning process 62 12,9524 ,68055 Source : Results obtained from SPSS software In this table, the average academic performance of first-year undergraduate students who involve metacognitive skills in their learning process is 14.415. 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