Learning With Computer-Based Learning Environments: A Literature Review of Computer Self-Efficacy

By Daniel C. Moos, Roger Azevedo. 2009

311 citations recorded by the source corpus.

Subfields: Education, Gender Studies, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/0ca6ec8a6480f776f8ac5bfa70d59d9dfcadb28f

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Citations in the corpus

Beyond cold technology: A systematic review and meta-analysis on emotions in technology-based learning environments (2018, background): “…of representation, (5) intelligent tutoring systems involving computational modeling of and adaptation to learner variables (e.g., learning progress), and/or (6) virtual/augmented rea-lities providing lifelike simulations of real or imaginary worlds (Lajoie & Azevedo, 2006; Moos & Azevedo, 2009).”
Interaction in distance education and online learning: using evidence and theory to improve practice (2011, background): “Finally, Moos and Azevedo (2009) summarized evidence on the positive association between students' computer selfefficacy beliefs and learning with educational software.”
Handbook of motivation at school (2009, background): “Self-efficacy also helps determine how much effort people expend on an activity, how long they persevere when confronting obstacles, and how resilient they are in the face of difficulties (Joët et al., 2011; Moos & Azevedo, 2009).”
The Role of Situational Interest in Personalized Learning (2018, background): “…prior knowledge, beliefs, interests, and motivations are known to influence the way they engage in computer-based learning tasks and the outcomes they obtain (e.g., Bernacki, Byrnes, & Cromley, 2012; Mitchell, Chen, & Macredie, 2005; Moos & Azevedo, 2009; Renninger, Hidi, & Krapp, 2014).”
Research in online and blended learning in the business disciplines: Key findings and possible future directions (2009, background): “…Kraiger, Stewart, & Wisher, 2006; Zhao, Lei, Yan, Lai, & Tan, 2005), recent literature reviews of online learning generally have ignored work originating from the business disciplines (Bernard et al., 2004; Larreamendy-Joerns & Leinhardt, 2006; Moos & Azevedo, 2009; Tallent-Runnels et al., 2006).”
Self-Efficacy Theory in Education (2016, background): “43 24 /9 78 13 15 77 33 84 .c h3 confronting obstacles, and how resilient they are in the face of difficulties (Joët et al., 2011; Moos & Azevedo, 2009).”
Students' ICT self-efficacy and computer and information literacy: Determinants and relationships (2018, background): “However, according to Moos and Azevedo (2009) computer self-efficacy is related to students’ learning processes and learning outcome.”
Measuring Cognitive and Metacognitive Regulatory Processes During Hypermedia Learning: Issues and Challenges (2010, background): “These theoretical discrepancies pose challenges for those interested in understanding and measuring regulatory processes during learning with hypermedia (see Azevedo, 2005, 2007, 2009; Greene & Azevedo, 2007, 2009; Moos & Azevedo, 2008, 2009).”
The study, evaluation, and improvement of university student self-efficacy (2016, methodology): “In addition to the strategies for improving self-efficacy reported here, readers are referred to reviews by Moos and Azevedo (2009), Pintrich (2003), Ponton et al. 1930 K. Bartimote-Aufflick et al. (2001), Usher and Pajares (2008), van Dinther, Dochy, and Segers (2011), and Zimmerman (2000b), for…”
Facilitating student engagement through the flipped learning approach in K-12: A systematic review (2020, background): “4 Students There are a range of internal psychosocial influences that influence student engagement (see Figure 11), including their technology acceptance and their prior ICT experience (Moos and Azevedo, 2009).”