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All Journal Tadris: Jurnal keguruan dan Ilmu Tarbiyah Online Learning in Educational Research
Amukune, Stephen
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Education

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Learning Motivation Mediates Growth Mindset, Self-Efficacy, and AI Usefulness Impact on Programming Problem-Solving Skills Fardan, Muhammad; Fathahillah, Fathahillah; Fakhri, M. Miftach; Sanatang, Sanatang; Adiba, Fhatiah; Soeharto, Soeharto; Amukune, Stephen
Tadris: Jurnal Keguruan dan Ilmu Tarbiyah Vol 10 No 1 (2025): Tadris: Jurnal Keguruan dan Ilmu Tarbiyah
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/tadris.v10i1.23743

Abstract

Artificial Intelligence has rapidly developed, especially in education and programming, providing advantages in improving learning efficiency and personalizing educational content. This study examines the relationships between learning motivation and problem-solving skills, as well as factors influencing learning motivation, namely growth mindset, self-efficacy, and perceived usefulness of Artificial Intelligence. Data collected from 276 students were analyzed using Partial Least Squares Structural Equation Modeling. The results show that growth mindset, self-efficacy, and perceived usefulness significantly influence learning motivation. Additionally, learning motivation strongly predicts problem-solving skills in programming tasks. These findings emphasize the critical role of psychological factors in fostering learning motivation and improving problem-solving abilities within Artificial Intelligence-enhanced programming environments. This research offers valuable insights for educators and instructional designers to develop effective strategies that integrate psychological support and Artificial Intelligence tools, ultimately enhancing student learning outcomes.
Harnessing Digital Skills For Academic Success: Unveiling The Power of Learning Motivation in Computational Thinking and Tech Integration Rauf, Annajmi; Fakhri, M. Miftach; Fathahillah, Fathahillah; Surianto, Dewi Fatmarani; Baso, Fadhlirrahman; Arifiyanti, Fitria; Amukune, Stephen
Online Learning In Educational Research (OLER) Vol 4, No 2 (2024): Online Learning in Educational Research
Publisher : CV FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/oler.v4i2.501

Abstract

The workforce's demand for critical thinking and innovation highlights the need to improve students' problem-solving skills, thus encouraging educational institutions to adopt technology-based strategies for an engaging learning environment. Previous studies have explored the relationship between learning motivation and academic outcomes and the role of technology and web-based media in improving problem-solving skills. However, limited research has comprehensively examined the interaction between computational thinking, technology integration, learning motivation, and student performance. This study aims to examine how Computational Thinking (CT) and Technology Integration (TI) influence Learning Motivation (LM) and Student Performance (SP), providing insights into optimizing digital skills for academic success in the digital age. Data were collected from 426 respondents' university students in Indonesia randomly. A questionnaire with a 5-point Likert scale consisting of several variables such as Computational Thinking, Technology Integration, Learning Motivation, and Student Performance were used in this study. Then, the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to check the measurement and assessment model. The results showed that CT and TI positively and significantly impacted LM and SP. In addition, LM serves as an important mediator, strengthening the influence of CT and IT on academic outcomes. Specifically, technology integration has a greater impact on LM than CT, while LM significantly improves SP. This study presents a detailed framework for educators to enhance learning experiences by integrating digital skills and fostering student motivation. The findings offer practical implications for developing effective educational strategies that meet the changing demands of the digital age. Future research is recommended to investigate the long-term effects of CT and IT in various educational environments.
The Impact of Organizational Culture, Socioeconomic Status, and Previous Technology Experience on AI Learning: Mediating Role of AI Anxiety Among University Students S, Aprilianti Nirmala; Rahman, Edi Suhardi; Fakhri, M Miftach; Surianto, Dewi Fatmarani; Baso, Fadhlirrahman; Arifiyanti, Fitria; Amukune, Stephen
Tadris: Jurnal Keguruan dan Ilmu Tarbiyah Vol 10 No 2 (2025): Tadris: Jurnal Keguruan dan Ilmu Tarbiyah
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/tadris.v10i1.23939

Abstract

This study explores the influence of AI anxiety, organizational culture, socioeconomic status (SES), and previous technology experience on AI learning outcomes among university students. Utilizing a quantitative approach, data were collected from 368 students via an online survey. Structural equation modeling (PLS-SEM) was employed to analyze the data, revealing that AI anxiety, often considered a barrier, can enhance learning outcomes when managed effectively. The study further highlights the significant direct and indirect roles of organizational culture and SES in shaping AI learning, with AI anxiety acting as a mediator. The results underscore the importance of designing educational strategies that foster a balance between institutional support and individual autonomy, while addressing disparities in technological access across different social strata. These findings offer valuable implications for developing more inclusive, accessible, and effective AI educational practices. The findings suggest that while AI anxiety is generally seen as a negative factor, its potential to motivate students when effectively managed can be leveraged to enhance learning engagement. Furthermore, the research emphasizes the need for targeted interventions and policies that ensure equitable access to AI tools, particularly for students from lower socioeconomic backgrounds, to foster a more inclusive learning environment.
Co-Authors Adiba, Fhatiah Arifiyanti, Fitria Baso, Fadhlirrahman Dewi Fatmarani Surianto Edi Suhardi Rahman Fardan, Muhammad Fathahillah Fathahillah M. Miftach Fakhri Rauf, Annajmi S, Aprilianti Nirmala Sanatang Soeharto Soeharto