Optimising Multimedia Learning: Effects of Pedagogical Agents' Appearance and Voice.
Background: In multimedia learning environments, pedagogical agents have emerged as an innovative tool to enhance digital instruction, yet optimising their design for maximal learning effectiveness remains underexplored. Objectives: This study aimed to investigate how specific design elements of ped...
| Publicado en: | Journal of Computer Assisted Learning Vol. 41; no. 4; pp. 1 - 26 |
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| Autores principales: | , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Aug2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=186918293&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 186918293 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Aug2025 vid: 41 iid: 4 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 186918293 186918293 186918293 10.1111/jcal.70101 186918293 ppf: 1 ppct: 25 formats: tig: atl: Optimising Multimedia Learning: Effects of Pedagogical Agents' Appearance and Voice. aug: au: Xiao, Mengshi Li, Weizi Han, Lei Zheng, Shasha affil: Faculty of Psychology, Shandong Normal University, Ji'nan Shandong,, China sug: subj: Multimedia Learning Methods Computer-Assisted Instruction Voice Evaluation Chatbot Educational Technology Outcomes of Education Human China Male Female Descriptive Statistics Confidence Intervals Two-Way Analysis of Variance Mediation Analysis P-Value Data Analysis Software Cues Social Perception Cognition Neural Transmission Eye Movement Measurements Motion Pictures Lecture Quality Improvement Funding Source Male Female ab: Background: In multimedia learning environments, pedagogical agents have emerged as an innovative tool to enhance digital instruction, yet optimising their design for maximal learning effectiveness remains underexplored. Objectives: This study aimed to investigate how specific design elements of pedagogical agents, namely appearance and voice type, affect multimedia learning performance. Methods: A 2 (appearance: formal vs. informal) × 2 (voice type: human vs. engine‐generated voice) between‐subjects design was employed, incorporating eye‐tracking technology. A total of 115 participants completed a multimedia learning module on chemical synaptic transmission. Learning outcomes were assessed using retention and transfer tests. Learner perceptions were measured across five indicators: social perception, perceived difficulty, lecture engagement, situational interest, and cognitive load. Results and Conclusions: Pedagogical agents with a formal appearance positively influenced learning outcomes, increasing fixation duration and fixation count, while reducing perceived material difficulty and intrinsic load. Agents with human voices similarly enhanced learning outcomes, increasing fixation counts, social perception, lecture engagement, and situational interest, while reducing perception difficulty, intrinsic load and extraneous load. The combination of a human voice and formal appearance produced the greatest benefits in learning performance. Meanwhile, compared to the combination of informal appearance and engine‐generated voice, the formal appearance with a human voice indirectly affected learning outcomes by reducing perceived difficulty, intrinsic load and extraneous load. It also indirectly increased fixation count through enhanced social perception, lecture engagement and situational interest. These findings advance our understanding of the role of pedagogical agents in multimedia learning and offer valuable insights for designing effective instructional tools that maximise engagement and learning outcomes. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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