Abstract
We studied the complexity of building a personalized and adaptive learning system for computer and information technology (CIT) curricula. Working with an online personalized competency-based CIT curriculum at Northern Arizona University (Flagstaff, Arizona, USA), our research developed a model for layering adaptive capacities into this curriculum to provide enhanced feedback and remediation for students. Additionally the model we developed provided integration of data collection and analysis that could drive evidence-based educational practices for CIT undergraduate and graduate programs. In this paper, we describe the conceptual model for a personalized-adaptive learning CIT educational environment, along with data collected over three years that support the efficacy of the approach we describe. We call the model SIGNAL CIT Education—Serial Integration of Guiding Nodes for Adaptive Learning in CIT Education.
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Tashiro, J., Hurst, F., Brown, A., Hung, P.C.K., Martin, M.V. (2014). Personalized-Adaptive Learning – A Model for CIT Curricula. In: Cheung, S.K.S., Fong, J., Zhang, J., Kwan, R., Kwok, L.F. (eds) Hybrid Learning. Theory and Practice. ICHL 2014. Lecture Notes in Computer Science, vol 8595. Springer, Cham. https://doi.org/10.1007/978-3-319-08961-4_25
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DOI: https://doi.org/10.1007/978-3-319-08961-4_25
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