The voice quality of pedagogical agent impacts learning and agent perceptions.
Background: The voices virtual on‐screen characters use has been shown to impact learning and perception outcomes. Recent replication research on these voices showed that synthetic voices were not a detriment if produced by a high‐quality engine with clear articulation. The current manuscript examin...
| Publicado en: | Journal of Computer Assisted Learning Vol. 40; no. 5; pp. 2278 - 2292 |
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| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Oct2024
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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=181038796&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 181038796 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Oct2024 vid: 40 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 181038796 177645945 181038796 181038796 10.1111/jcal.13027 181038796 ppf: 2278 ppct: 14 formats: tig: atl: The voice quality of pedagogical agent impacts learning and agent perceptions. aug: au: Siegle, Robert F. Craig, Scotty D. affil: Human Systems Engineering, Ira A. Fulton Schools of Engineering, Arizona State University, Mesa Arizona, , USA sug: subj: Voice Quality Evaluation Learning Methods Educational Technology User-Computer Interface Speech Acoustics Perception Human Male Female Adolescence Adult Middle Age Aged Aged, 80 and Over United States Computer-Assisted Instruction Hearing Physiology Multimedia Education Outcomes of Education Crowdsourcing Transfer (Psychology) Avatars Methods Cost Effectiveness Analysis Accents and Dialects Deep Learning Methods Sociological Theory Questionnaires Self Report Interrater Reliability Experimental Studies Descriptive Statistics Comparative Studies Summated Rating Scaling Analysis of Variance kappa Statistic Adolescent: 13-18 years Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Aged, 80 & over Male Female ab: Background: The voices virtual on‐screen characters use has been shown to impact learning and perception outcomes. Recent replication research on these voices showed that synthetic voices were not a detriment if produced by a high‐quality engine with clear articulation. The current manuscript examines previous accent research that utilized now outdated engines, to determine if the impact of accents still holds with high‐quality engines and voice actors. Objectives: To investigate the impact on learning and perceptions with pedagogical agents speaking in accented voices, synthetic voices, and the interaction between the two using modern voice engines. Methods: This study is a between‐subjects two (accent) by two (type) factorial design to determine the impact the voice accent, voice type, and the interaction have on learning retention, learning transfer, mental effort efficiency, and perception measures. 197 participants were recruited from the online Amazon's Mechanical Turk with qualifications of 18 years of age, "normal or corrected‐to‐normal hearing", and located with the continental United States of America. Results and Conclusions: There were no significant differences between the accented conditions or interaction effects, deviating from previous research that showed impact of accents on learning. The synthetic condition had significantly lower knowledge retention, knowledge transfer, mental effort efficiency, and perception measures than the human professional. These findings demonstrate the importance of considering voice quality when designing pedagogical agents. Previous research showed synthetic voices perform as well as the average voice, and this research continues the narrative of voice quality by showing professional recordings outperform modern synthetic engines. Lay Description: What is currently known about this topic: Accents and synthetic voices can impact learning from virtual humans. What does this paper add: Shows professional human voices outperform modern synthetics, a quality effect. Implications for practice/or policy: Creators of educational materials should aim for professional voice actors. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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