A task-technology fit view of learning management system impact

By T. McGill, Jane E. Klobas. Comput. Educ., 2009

558 citations recorded by the source corpus.

Subfields: Computer Science Applications, Developmental and Educational Psychology, Education

View Paper: https://www.semanticscholar.org/paper/57ee60f53cefabbf6c17a4225c2e21c6c58b0b4e

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In Computer Science Applications

In Developmental and Educational Psychology

In Education

Citations in the corpus

Antecedents and consequences of e‐learning acceptance (2011, background): “…the LMS can process, store and disseminate learning materials and support administration and communication associated with teaching and learning (McGill & Klobas, 2009), and it allows users to control the pace of the training and to tailor learning according to their individual needs (Baylari &…”
A meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types (2011, background): “Study Sample size User type E-learning technology type Theory Brown (2002) 73 Students E-learning System (WebCT) TAM Lee, Cho, Gay, and Davidson (2003) 31 Students E-learning Technology/Tool (Web Based Collaboration in Virtual Learning Environment) TAM Yi and Hwang (2003) 109 Students E-learning Sys”
Saving time or innovating practice: Investigating perceptions and uses of Learning Management Systems (2009, background): “Understanding both instructor and student perceptions is important for evaluating the potential success of the LMS (McGill & Klobas, 2009).”
Let’s not forget: Learning analytics are about learning (2014, background): “As such, any counts of log-ins, tools and resources within the LMS course site, were effectively redundant for this particular course.”
Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives (2012, methodology): “Overall , I intend to continue use the VLS Positive impacts on learning ( 1 : Strongly Disagree ; 5 : Strongly Agree ) ( McGill and Klobas , 2009 ) 1 .”