Abdullahi Yusuf
5 Publications in AERD
Author Publications
Export PDFImplementing a proposed framework for enhancing critical thinking skills in synthesizing AI-generated texts
By Abdullahi Yusuf
Since the development of open and low-cost generative artificial intelligence (GenAI), the higher education community has witnessed high use of AI-generated texts in scholarly research and academic assignments, attracting ongoing debate about whether such practices constitute cheating. While scholars argue that integrating GenAI tools can enhance productivity, critics raise concerns about the negative effect of such integration on critical thinking (CrT). This study therefore proposed a framework for enhancing students’ CrT skills in synthesizing AI-generated information. The proposed framework is underpinned by various theoretical foundations, encompassing five interconnected step-wise phases (familiarizing, conceptualizing, inquiring, evaluating, and synthesizing). The study was conducted under two separate experiments. The first experiment (Study 1) validated the effectiveness of the proposed framework, providing CrT training to 179 postgraduate students. In the second study (n = 125), additional experiments were undertaken to confirm the effectiveness of the framework in different contexts. An experimental procedure involving pretest and posttest design was implemented wherein participants were randomly allocated to one of three groups: experimental group 1 (exposed to our framework), experimental group 2 (exposed to an alternative self-regulated learning framework), and a control group (exposed to a non-structured framework). Results from Study 1 revealed that the framework enhances students’ CrT skills to synthesize AI-generated texts. However, these CrT skills manifested through various rigorous training aimed at reinforcing learning. While the proposed framework holds considerable value in cultivating CrT skills, significant differences arise across various personality traits. In Study 2, the framework proved to be effective in different contexts. However, it did not make a difference, particularly in its capacity to enhance students’ self-regulated learning compared to other frameworks. We discussed the implications of the findings and recommended it to educators seeking to prepare students for the challenges of the AI-driven knowledge economy. © 2024 Elsevier Ltd
Using multimodal learning analytics to model students' learning behavior in animated programming classroom
By Abdullahi Yusuf
Studies examining students' learning behavior predominantly employed rich video data as their main source of information due to the limited knowledge of computer vision and deep learning algorithms. However, one of the challenges faced during such observation is the strenuous task of coding large amounts of video data through repeated viewings. In this research, we confirm the possibilities of classifying students' learning behavior using data obtained from multimodal distribution. We employed computer algorithms to classify students' learning behavior in animated programming classrooms and used information from this classification to predict learning outcomes. Specifically, our study indicates the presence of three clusters of students in the domain of stay active, stay passive, and to-passive. We also found a relationship between these profiles and learning outcomes. We discussed our findings in accordance with the engagement and instructional quality models and believed that our statistical approach will support the ongoing refinement of the models in the context of behavioral profiling and classroom interaction. We recommend that further studies should identify different epistemological frames in diverse classroom settings to provide sufficient explanations of students' learning processes.
Generative AI in education and research: A systematic mapping review
By Abdullahi Yusuf
Given the potential applications of generative AI (GenAI) in education and its rising interest in research, this systematic review mapped the thematic landscape of 407 publications indexed in the Web of Science, ScienceDirect and Scopus. Using EPPI Reviewer, publication type, educational level, disciplines, research areas and applications of GenAI were extracted. Eight discursive themes were identified, predominantly focused on 'application, impact and potential', 'ethical implication and risks', 'perspectives and experiences', 'institutional and individual adoption', and 'performance and intelligence'. GenAI was conceptualised as a tool for 'pedagogical enhancement', 'specialised training and practices', 'writing assistance and productivity', 'professional skills and development', and as an 'interdisciplinary learning tool'. Key gaps highlighted include a paucity of research and discussions on GenAI in K-12 education; a limited exploration of GenAI's impact using experimental procedures; and a limited exploration of the potential and ethical concerns of GenAI from the lens of cultural dimensions. Promising opportunities for future research are highlighted.
Revising the computer programming attitude scale in the context of attitude ambivalence
By Abdullahi Yusuf
Background: Several attitude scales have been developed to measure students' attitudes toward computer programming, including the prominent one developed by Cetin and Ozden. The development of these scales stemmed from the elusive nature of attitude and the lack of specific constructs to measure attitude. These instruments measure students' attitudes based on one-dimensional perspective, thus, making it difficult to interpret the meaning of some attitude evaluations such as the meaning of neutral points in a 10-point scale (for example).Objectives: The computer programming attitude scale was modified to measure ambivalence. The study also investigate attitude differences across demographic variables and used these variables to predict ambivalence.Methods: The study was conducted in two phases. In the first phase, the instrument was validated using exploratory factor analysis and confirmatory factor analysis. In the second phase, the revised scale was administered to another 547 students in four research universities for empirical investigation.Results: Results show that the instrument is valid and suitable for measuring students' programming attitudes. Participants' attitudes skewed toward the negative attitude dimension. Lastly, we found that both attitude and ambivalence are factors of programming experience.Conclusions: We discussed the findings, recommend the instrument to programming tutors, and strongly emphasise the evaluation of students' ambivalent attitudes.
Research trends on learning computer programming with program animation: A systematic mapping study
By Abdullahi Yusuf
Over the last few decades, computer programming has become an important field of endeavor due to rapid development in the information sector. Despite the importance of programming, there is a growing concern that it is relatively difficult. In the process, researchers have started employing media tools to reduce programming difficulties and motivate learners to approach programming problems. One of the common tools widely used is program animation-an instructional medium that incorporates animated characters. However, little is known about the research trends in this field of study. This article, therefore, employed a systematic mapping method to review this trend to find patterns and gaps left in the literature. The study extracted 48 articles published between 2000 and 2022 from four scientific databases (Web of Science, Scopus, ScienceDirect, and ERIC) and three digital libraries (ACM Digital Library, IEEE Xplore Digital Library, and Wiley Online Library). The review discovered important trends. First, there is a paucity of research evidence evaluating program animation in the context of secondary and elementary levels; the majority of the extracted studies focused on participants from tertiary institutions. A similar paucity of research evidence employing mixed methods and qualitative approaches was also noted. Scratch programs were used in recent research more often than other program animations. There is also too little evaluation of psychomotor variables. Finally, there exist inconsistent findings on the effect of program animation although plenty of studies revealed positive results in favor of these media tools. The study therefore recommends that future research should be conducted to fill these identified gaps.
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