SynthesisF1000Research2026
Emerging Technologies in Higher Education Course Development: A Systematic Review of Design Frameworks, Learning Outcomes, and Pedagogical Integration.
Synthesis in F1000Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review explored the impact of technology on course design, student learning outcomes, and engagement in higher education. The major enablers and barriers to implementation are also discussed. Following the PRISMA 2020 procedure, the systematic review integrated findings from 76 peer-reviewed empirical studies from 1996 to 2025. A mixed-method narrative and quantitative synthesis supported by statistical conversions mean standardized effect estimate (Cohen's d) to enable cross-study comparison was used. Results showed that technology-involved instruction could be most effective with integration of an existing instructional design model. Technological Pedagogical Content Knowledge (TPACK); Utilization of Constructive Alignment (CA); Analyze, Design, Develop, Implement, and Evaluate (ADDIE), Design-Based Research (DBR) revealed moderate-to-high effects on learning outcome (d = 0.65-0.74), while deep learning model with embedded artificial intelligence (AI) and mixed/extended reality (MR) reported the highest effect (d = 1.30). For technology categories, the strongest effects on learning and engagement observed at immersive technologies (AR/VR/MR) (g = 0.98), followed by AI, and learning analytics (g = 0.62), and game-based learning (g = 0.71). Improvement in engagement was common across studies, while long-term behavioral and transfer effects were little observed. Success indicators identified were pedagogical alignment, institutional readiness, faculty competence, learner preparedness, whereas the challenges were infrastructure constraints, digital divides, and inadequate longitudinal evaluation. Synthesizing these through the lens of socio-technical systems perspective, results indicate that educational effectiveness is outcome of the relationship between technological affordances, pedagogical design, and organizational capacity.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.