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All Journal Indonesian Science Education Journal (ISEJ) Journal of Educational Research, Evaluation and Supervision
Novarita Novarita
Universitas Lampung
Agriculture, Biological Sciences & Forestry Education Other

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Meta Evaluation: On The Evaluation of Academic Services and Facilities at FKIP Baturaja University Dewi Lestari; Novarita Novarita; Undang Rosidin
Journal of Educational Research, Evaluation and Supervision Vol. 1 No. 1 (2024): Journal of Educational Research, Evaluation and Supervision
Publisher : Foundation of Jannatun Naim Lampung

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Abstract

The success of universities in achieving their vision and mission is determined by student satisfaction with the services provided by universities. This study aims to reveal the quality of college services to students. Through a qualitative approach, this researcher uses data sources in the form of questionnaires that are surveyed to students and then processed descriptively, which are converted in the form of a rating scale. The target of the student satisfaction survey on university services is active students at Baturaja University, involving 797 people from the total number of students (the student body). The data collected were in the form of questionnaires distributed to five faculties and one postgraduate program. The method used in this research is the survey method. A survey is one type of research used to examine the symptoms of a group or individual behavior. In surveys, data collection generally uses a questionnaire as a data collection tool with the aim of knowing who, what the respondent thinks, feels, or the tendency of an action. The results of this study indicate that the level of student satisfaction with Baturaja University services in each faculty, in general, for 4 service categories is in the moderately satisfactory category.
Online Collaborative Learning With Deep Learning In Fostering Critical Thinking And Motivation: Meta Synthetic Analysis Novarita Novarita; Abdurrahman Abdurrahman; Cucu Sutarsyah; Budi Kadaryanto; Bambang Setiyadi
ISEJ : Indonesian Science Education Journal Vol. 7 No. 2 (2026): February-May
Publisher : Yayasan Darussalam Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62159/isej.v7i2.2052

Abstract

Online learning has expanded rapidly, yet many digital courses still struggle to cultivate sustained motivation and higher-order thinking because interaction is often limited to content delivery, fragmented discussion, or individual task completion. This article develops an integrative meta-synthesis on how Online Collaborative Learning (OCL), when supported by deep-learning-enabled artificial intelligence (AI), can strengthen critical thinking and learner motivation in higher education. The review synthesizes theoretical and empirical literature on OCL, computer-supported collaborative learning, learning analytics, adaptive feedback, and self-determination theory. Rather than treating AI as a replacement for pedagogy, this article conceptualizes deep learning as an adaptive scaffolding layer that can support peer dialogue, feedback, grouping, early-warning signals, and personalized learning paths. The synthesis identifies four mechanisms through which OCL-AI integration may enhance learning: argumentative knowledge construction, socially shared regulation, adaptive formative feedback, and motivational need support. The article also argues that these benefits are conditional on ethical data governance, transparent algorithms, teacher facilitation, and equitable access to digital infrastructure. The proposed framework contributes to online pedagogy by clarifying the relationship between social collaboration and machine-supported personalization. It offers practical design principles for lecturers, instructional designers, and higher education institutions seeking to develop online learning environments that are cognitively challenging, motivationally supportive, and ethically responsible.
Co-Authors Abdurahman Abdurrahman Bambang Setiyadi Budi Kadaryanto Cucu Sutarsyah Dewi Lestari Undang Rosidin