Technology-enabled Learning in Digital Education: Research Areas and Prediction Trends of Learning Technologies for Authentic Assessments Practices

Abstract

This study aims to provide practical insights on the research areas and prediction trends of learning technologies that support authentic assessment practices in the digital education setting. Technology-enabled learning can be utilized to enhance assessment design in meaningful ways that resembles the professional work environment. Innovative technology-enabled assessment practices necessitate an understanding of the technologies at-hand, hence a disciplined inquiry is called upon into the multitude of technologies that define the landscape. The study looked to investigate the technology groups and research efforts within the field of learning technologies that were shaping digitally mediated authentic assessment practices. Using Horizon Report (HR), an annual education-based technology forecasting publication, as a reference, the study looked to evaluate if HR is a good proxy to predict the evolution of learning technologies in the said scape. Research distinguished four key learning technology groups, namely ubiquitous learning technology, adaptive learning technology, immersive learning technology, and learning object. Network analyses performed on the four technology groups identified key generalizable research themes that can be utilized for research focus. The study also found that HR is a useful tool to predict technology trends, as corroborated from bibliometric analyses, and detailed the composition and evolution of these trends. This study can help educators and researchers identify and decide promising potential areas for future research and/or investment focus.

La inteligencia artificial en la educación y sus implicaciones: un mapeo sistemático de la literatura

“…El estudio analiza la aplicación de la inteligencia artificial para el mejoramiento de los procedimientos de enseñanza y aprendizaje en ambientes educativos, además de explorar sus repercusiones. Se destaca que la inteligencia artificial puede mejorar la eficiencia y la precisión de la evaluación educativa al analizar grandes cantidades de datos y proporcionar retroalimentación personalizada a los estudiantes (Lim et al, 2023). El artículo también aborda cuestiones éticas desafiantes relacionadas con la implementación de la inteligencia artificial en la evaluación educativa, tales como la protección de la privacidad de los datos de los estudiantes, la equidad en el acceso a la tecnología y la toma de decisiones fundamentada en algoritmos.…”

Konsep Penilaian Autentik dalam Evaluasi Pembelajaran di Sekolah Dasar

“…Penggunaan penilaian autentik dalam penilaian pembelajaran di sekolah dasar menjadi penting karena beberapa alasan. Pertama, penilaian autentik dapat menciptakan situasi belajar yang lebih bermakna bagi siswa karena lebih erat kaitannya dengan kehidupan siswa sehari-hari (Farrell, 2020;Lim, 2022). Kedua, penilaian autentik menggambarkan kemampuan siswa dalam menerapkan pengetahuan dan keterampilannya pada situasi dunia nyata, memberikan gambaran yang lebih akurat mengenai penguasaannya terhadap materi pelajaran.…”

Assessment Model in Indonesian Language Learning Based on The Merdeka Curriculum at Junior High School in Banyuwangi Regency

“…Other studies of learning assessment in the Merdeka Curriculum are limited. Studies related to learning assessment, in general, have been carried out, including an analysis of the principles of assessment in the Merdeka Curriculum (Ritonga, 2023), self-assessment activities in IEFL classes (Kumar et al, 2023), the Digital Competencies for Teaching in Science Education (DiKoLAN) framework as a foundation for self-evaluation (Kotzebue et al, 2021), language learner self-assessment (Butler et al, 2023), deep programmed assessment of overall learning and practice (Warm et al, 2022), formative assessment based on higher-order thinking skills (HOTS) (Wiyaka et al, 2020), authentic assessment of digital learning (Lim et al, 2022), and investigations of self-assessment in higher education (Ifenthaler et al, 2021).…”