{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/108160"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/108160","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Examining technological factors on e-learning acceptance and learning transfer","abstract":"As the body of e-learning literature grows, our understanding of how e-learning works and how we make e-learning better became deeper and more complex. Although various factors affecting e-learning have been studied, our understanding of technological factors that are unique in e-learning such as computer anxiety, perceived ease of use, or controllability is still incomplete due to the ambiguous boundaries in definitions and a lack of understanding of their effects on learning outcomes. Furthermore, only a few e-learning acceptance studies have provided an integrated outlook of the e-learning system. The overall purpose of this study is to explore technological factors at the learner, instructional design, and system level and examine their effects on the e-learning acceptance and learning outcomes. The effects of eight technological factors on perceived usefulness, perceived ease of use, learner satisfaction, intention to use, actual use, and transfer motivation were measured with Structural Equation Modeling (SEM) using AMOS (version 26). 331 online MBA program students participated in the study. The result could not find the significant effects of learner’s previous technology experience or anxiety, but technology self-efficacy was found to be significant. The results highlighted the importance of instructional design and e-learning system. e-Learning providers should not only ensure the reliability of the e-learning system, but also consider providing extra features including controllability and technical support. In addition, the results suggested that the usage of the e-learning system does not guarantee learning transfer, but the usefulness of the e-learning system may facilitate both acceptance and learning transfer. Finally, the confirmatory factor analysis result indicated the need for developing better measurements for technological factors. Theoretical and practical implications from findings, limitations, and future research suggestions are discussed.","abstract_html":"As the body of e-learning literature grows, our understanding of how e-learning works and how we make e-learning better became deeper and more complex. Although various factors affecting e-learning have been studied, our understanding of technological factors that are unique in e-learning such as computer anxiety, perceived ease of use, or controllability is still incomplete due to the ambiguous boundaries in definitions and a lack of understanding of their effects on learning outcomes. Furthermore, only a few e-learning acceptance studies have provided an integrated outlook of the e-learning system. The overall purpose of this study is to explore technological factors at the learner, instructional design, and system level and examine their effects on the e-learning acceptance and learning outcomes. The effects of eight technological factors on perceived usefulness, perceived ease of use, learner satisfaction, intention to use, actual use, and transfer motivation were measured with Structural Equation Modeling (SEM) using AMOS (version 26). 331 online MBA program students participated in the study. The result could not find the significant effects of learner’s previous technology experience or anxiety, but technology self-efficacy was found to be significant. The results highlighted the importance of instructional design and e-learning system. e-Learning providers should not only ensure the reliability of the e-learning system, but also consider providing extra features including controllability and technical support. In addition, the results suggested that the usage of the e-learning system does not guarantee learning transfer, but the usefulness of the e-learning system may facilitate both acceptance and learning transfer. Finally, the confirmatory factor analysis result indicated the need for developing better measurements for technological factors. Theoretical and practical implications from findings, limitations, and future research suggestions are discussed.","abstract_has_math":false,"creators":["Wong, Seohyun Claire"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Human Resource Education","degree_department":null,"school":null,"contributors":["Li, J. Jessica","Huang, Wen-Hao David","Scagnoli, Norma I.","Xia, Yan"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-08-26T23:58:39Z","date_published":"2020-08-26T23:58:39Z","updated_at":"2026-07-22T22:24:47Z","subjects":["Keywords: e-learning, technological factors, e-learning acceptance, learning transfer, e-learning effectiveness"],"languages":["en"],"rights":["Copyright 2020 Seohyun Claire Wong"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/108160","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Li, J. 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Although various factors affecting e-learning have been studied, our understanding of technological factors that are unique in e-learning such as computer anxiety, perceived ease of use, or controllability is still incomplete due to the ambiguous boundaries in definitions and a lack of understanding of their effects on learning outcomes. Furthermore, only a few e-learning acceptance studies have provided an integrated outlook of the e-learning system. The overall purpose of this study is to explore technological factors at the learner, instructional design, and system level and examine their effects on the e-learning acceptance and learning outcomes. The effects of eight technological factors on perceived usefulness, perceived ease of use, learner satisfaction, intention to use, actual use, and transfer motivation were measured with Structural Equation Modeling (SEM) using AMOS (version 26). 331 online MBA program students participated in the study. The result could not find the significant effects of learner’s previous technology experience or anxiety, but technology self-efficacy was found to be significant. The results highlighted the importance of instructional design and e-learning system. e-Learning providers should not only ensure the reliability of the e-learning system, but also consider providing extra features including controllability and technical support. In addition, the results suggested that the usage of the e-learning system does not guarantee learning transfer, but the usefulness of the e-learning system may facilitate both acceptance and learning transfer. Finally, the confirmatory factor analysis result indicated the need for developing better measurements for technological factors. Theoretical and practical implications from findings, limitations, and future research suggestions are discussed.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2022-05-01","The student, Seohyun Claire Wong, accepted the attached license on 2020-05-06 at 00:22.","The student, Seohyun Claire Wong, submitted this Dissertation for approval on 2020-05-06 at 00:33.","This Dissertation was approved for publication on 2020-05-07 at 08:56.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15238 on 2020-08-25 at 17:29:48","Made available in DSpace on 2020-08-26T23:58:39Z (GMT). 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The overall purpose of this study is to explore technological factors at the learner, instructional design, and system level and examine their effects on the e-learning acceptance and learning outcomes. The effects of eight technological factors on perceived usefulness, perceived ease of use, learner satisfaction, intention to use, actual use, and transfer motivation were measured with Structural Equation Modeling (SEM) using AMOS (version 26). 331 online MBA program students participated in the study. The result could not find the significant effects of learner’s previous technology experience or anxiety, but technology self-efficacy was found to be significant. The results highlighted the importance of instructional design and e-learning system. e-Learning providers should not only ensure the reliability of the e-learning system, but also consider providing extra features including controllability and technical support. In addition, the results suggested that the usage of the e-learning system does not guarantee learning transfer, but the usefulness of the e-learning system may facilitate both acceptance and learning transfer. Finally, the confirmatory factor analysis result indicated the need for developing better measurements for technological factors. Theoretical and practical implications from findings, limitations, and future research suggestions are discussed.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2022-05-01","The student, Seohyun Claire Wong, accepted the attached license on 2020-05-06 at 00:22.","The student, Seohyun Claire Wong, submitted this Dissertation for approval on 2020-05-06 at 00:33.","This Dissertation was approved for publication on 2020-05-07 at 08:56.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15238 on 2020-08-25 at 17:29:48","Made available in DSpace on 2020-08-26T23:58:39Z (GMT). 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