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Previous research studies, which were performed under different task environments, identified a variety of factors that can affect student satisfaction with e-learning courses. Lifelong e-learning courses can be different from typical e-learning courses because they are designed to provide lifelong, voluntary, and self-motivated pursuit of knowledge for either personal or professional reasons. This study uses three popular behavioral models to identify factors that can affect student intent to continue in a lifelong e-learning course. The study integrates elements of the TAM, TPB, and PCI models to create a research model. The study uses the research model to predict student intent to continue in a lifelong e-learning course. The study uses random selection to choose students from members of the SME Online University in Taiwan. The study uses a survey to collect information concerning student intent to continue in a lifelong e-learning course. The study uses a partial least squares structural (PLS) model to analyze survey results. Study results show that two factors (perceived usefulness and compatibility) have significant impacts on student intent to continue in a lifelong e-learning course. Study results also show that the PCI model predicts student intent to continue in a lifelong e-learning course more accurately than the TAM and TPB models.
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Stored only when both papers are in the corpus — 7 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.