July - December 2026

This study aims to explore the perceptions of Islamic Education students toward online learning and its contribution to students' social skills. Online learning is a form of technology-based educational innovation widely used in higher education. However, its implementation generates various perceptions among students, which are believed to influence their social abilities in interacting, communicating, and adapting within both academic and social environments. This research uses a quantitative approach with a correlational descriptive method. The research population is all students of the Islamic Religious Education Study Program, while the research sample is taken using specific sampling techniques according to the research needs. Data collection techniques are carried out through questionn aires, observations, and documentation. Data analysis uses validity and reliability tests, descriptive analysis, as well as correlation tests to determine the contribution of students' perceptions to the level of Spiritual Quotient. The research results indicate that the perception of Islamic Education students towards online learning falls into the fairly good category. Students assess that online learning provides easy access to materials and flexibility in study time, but there are still obstacles in interaction and understanding of learning materials. The analysis results show that there is a positive contribution between students perception of online learning and the level of Spiritual Quotient. The more positive the students perception of online learning, the better the level of Spiritual Quotient possessed by the students.

This systematic review examines recent empirical studies (2021–2026) on innovative teaching methods in primary earth and space science, focusing on student conceptual understanding and engagement. Using PRISMA 2020 guidelines, we searched major academic databases (Scopus, Web of Science, ERIC, ScienceDirect, etc.) for peer-reviewed articles. Our thematic synthesis reveals that inquiry-based, project-based, STEM/STEAM, game-based, and digital learning approaches (including augmented/virtual reality) are frequently implemented. For example, STEAM-first instruction was shown to promote deeper conceptual change than STEM-only methods, and AR-based activities consistently enhanced understanding, motivation, and collaboration. Immersive technologies (AR/VR) improve visualization of abstract concepts and boost engagement, often achieving large effect sizes on learning and self-efficacy. Game-based learning also yields moderate-to-large benefits on cognitive and affective outcomes. Teachers’ perceptions and training emerged as crucial: professional development improved educators’ ability to design hands-on STEM tasks and increased student motivation. Reported challenges include teacher content knowledge gaps and resource constraints. Despite positive results, gaps remain in understanding long-term impacts, cross-context generalizability, and the combined effects of multiple innovations. We synthesize practical implications–urging curriculum developers and policymakers to support teacher training, integrate technology (e.g. AR simulations) thoughtfully, and foster environments for inquiry and collaboration. Future research should explore diverse contexts and emerging tools to further enhance earth and space science literacy in primary students.

The proliferation of generative artificial intelligence (generative AI) tools has shaken the fundamental assumptions of learning evaluation in higher education, particularly the premise that a piece of writing submitted by a student reliably reflects that individual's own competence. This study employs a qualitative design with a library research approach to examine how the field of learning evaluation is responding to this disruption, focusing on three areas: (1) the redesign of assessment instruments toward AI-resistant authentic tasks; (2) the validity and reliability of AI detection instruments used to safeguard evaluation integrity; and (3) the paradigm shift from summative toward formative evaluation enabled by generative AI-based feedback. Data were collected from indexed journals, one international-scale multi-tool empirical study, and classical evaluation theory literature published between 2011 and 2025, and were subsequently analyzed thematically. The findings indicate that the assessment redesign literature converges on process-oriented and higher-order thinking tasks that are structurally difficult to fully automate, in line with constructive alignment theory. However, empirical testing of AI detection tools reveals serious reliability issues, with accuracy rates below 80% for the majority of tools tested, as well as documented risks of false accusation, rendering such tools unsuitable as the sole evidence in high-stakes evaluation decisions. Meanwhile, automated feedback based on generative AI shows potential for scaling rapid formative feedback, although its pedagogical quality remains variable and continues to require human oversight. This study concludes that an accountable evaluation system in the era of generative AI must simultaneously redesign the object being assessed, treat detection technology as supporting rather than definitive evidence, and redirect the culture of evaluation from summative gatekeeping toward sustainable and dialogic formative practice.