“…Chatbots have caught the attention of language teaching researchers due to their capacity to communicate with users in the target language (Fryer et al, 2019;Jia, Chen, Ding, & Ruan, 2012;Tegos, Demetriadis, & Karakostas, 2015). Chatbot-supported language learning refers to the use of a chatbot to interact with students using natural language for daily language practice (e.g., conversation practice; Fryer et al, 2017), answering language learning questions (e.g., storybook reading; Xu, Wang, Collins, Lee, & Warschauer, 2021) and conducting assessment and providing feedback (e.g., vocabulary test; Jia et al, 2012). With the help of visual chatbot development platforms, teachers can create chatbots by themselves without prior programming experience.…”
Section: A Niche For Chatbots In Language Learningmentioning
confidence: 99%
“…The results showed that English was the dominant language in the use of chatbots for students' language learning. Among 23 studies involving chatbots used for English learning, three of them were for language literature for native English speakers (Lin & Chang, 2020;Xu et al, 2021;Xu & Warschauer, 2020); the other 20 studies involved the teaching of English as a foreign language (EFL) or second language (ESL). One study involved the teaching of Chinese as a second language.…”
Background: The use of chatbots as learning assistants is receiving increasing attention in language learning due to their ability to converse with students using natural language. Previous reviews mainly focused on only one or two narrow aspects of chatbot use in language learning. This review goes beyond merely reporting the specific types of chatbot employed in past empirical studies and examines the usefulness of chatbots in language learning, including first language learning, second language learning, and foreign language learning. Aims: The primary purpose of this review is to discover the possible technological, pedagogical, and social affordances enabled by chatbots in language learning.Materials & Methods: We conducted a systematic search and identifies 25 empirical studies that examined the use of chatbots in language learning. We used the inductive grounded approach to identify the technological and pedagogical affordances, and the challenges of using chatbots for students' language learning. We used Garrison's social presence framework to analyze the social affordances of using chatbots in language learning Results: Our findings revealed three technological affordances: timeliness, ease of use, and personalization; and five pedagogical uses: as interlocutors, as simulations, for transmission, as helplines, and for recommendations. Chatbots appeared to encourage students' social presence by affective, open, and coherent communication. Several challenges in using chatbots were identified: technological limitations, the novelty effect, and cognitive load.
Discussion and Conclusion:A set of rudimentary design principles for chatbots are proposed for meaningfully implementing educational chatbots in language learning, and detailed suggestions for future research are presented.
“…Chatbots have caught the attention of language teaching researchers due to their capacity to communicate with users in the target language (Fryer et al, 2019;Jia, Chen, Ding, & Ruan, 2012;Tegos, Demetriadis, & Karakostas, 2015). Chatbot-supported language learning refers to the use of a chatbot to interact with students using natural language for daily language practice (e.g., conversation practice; Fryer et al, 2017), answering language learning questions (e.g., storybook reading; Xu, Wang, Collins, Lee, & Warschauer, 2021) and conducting assessment and providing feedback (e.g., vocabulary test; Jia et al, 2012). With the help of visual chatbot development platforms, teachers can create chatbots by themselves without prior programming experience.…”
Section: A Niche For Chatbots In Language Learningmentioning
confidence: 99%
“…The results showed that English was the dominant language in the use of chatbots for students' language learning. Among 23 studies involving chatbots used for English learning, three of them were for language literature for native English speakers (Lin & Chang, 2020;Xu et al, 2021;Xu & Warschauer, 2020); the other 20 studies involved the teaching of English as a foreign language (EFL) or second language (ESL). One study involved the teaching of Chinese as a second language.…”
Background: The use of chatbots as learning assistants is receiving increasing attention in language learning due to their ability to converse with students using natural language. Previous reviews mainly focused on only one or two narrow aspects of chatbot use in language learning. This review goes beyond merely reporting the specific types of chatbot employed in past empirical studies and examines the usefulness of chatbots in language learning, including first language learning, second language learning, and foreign language learning. Aims: The primary purpose of this review is to discover the possible technological, pedagogical, and social affordances enabled by chatbots in language learning.Materials & Methods: We conducted a systematic search and identifies 25 empirical studies that examined the use of chatbots in language learning. We used the inductive grounded approach to identify the technological and pedagogical affordances, and the challenges of using chatbots for students' language learning. We used Garrison's social presence framework to analyze the social affordances of using chatbots in language learning Results: Our findings revealed three technological affordances: timeliness, ease of use, and personalization; and five pedagogical uses: as interlocutors, as simulations, for transmission, as helplines, and for recommendations. Chatbots appeared to encourage students' social presence by affective, open, and coherent communication. Several challenges in using chatbots were identified: technological limitations, the novelty effect, and cognitive load.
Discussion and Conclusion:A set of rudimentary design principles for chatbots are proposed for meaningfully implementing educational chatbots in language learning, and detailed suggestions for future research are presented.
“…But, evidently, whether the integration of humanlike design components is desirable also depends on the concrete applications for which technological entities are used (e.g., (Złotowski et al, 2015;Choi & Kim, 2009;Collins, 2017;Goetz et al, 2003;Riether et al, 2012)), especially in the context of child-technology engagements (Pearson & Borenstein, 2014). For example, although social robots have proven their promising potential as learning technologies (for reviews see (Belpaeme et al, 2018;Kanero et al, 2018;Papadopoulos et al, 2020)) -and this seems to hold true for DVAs as well (e.g., (Xu et al, 2021)) -children can also develop adverse responses to too much human-likeness (e.g., (Brink et al, 2019;Woods, 2006;Yip et al, 2019)), therefore echoing Mori's (Mori, 2012) widely-cited 'uncanny valley' theorem about the eeriness of almost perfect human resemblance.…”
Section: What Are Its Consequences? Anthropomorphism From a Normative Research Perspectivementioning
Abstract‘Anthropomorphism’ is a popular term in the literature on human-technology engagements, in general, and child-technology engagements, in particular. But what does it really mean to ‘anthropomorphize’ something in today’s world? This conceptual review article, addressed to researchers interested in anthropomorphism and adjacent areas, reviews contemporary anthropomorphism research, and it offers a critical perspective on how anthropomorphism research relates to today’s children who grow up amid increasingly intelligent and omnipresent technologies, particularly digital voice assistants (e.g., Alexa, Google Assistant, Siri). First, the article reviews a comprehensive body of quantitative as well as qualitative anthropomorphism research and considers it within three different research perspectives: descriptive, normative and explanatory. Following a brief excursus on philosophical pragmatism, the article then discusses each research perspective from a pragmatistic viewpoint, with a special emphasis on child-technology and child-voice-assistant engagements, and it also challenges some popular notions in the literature. These notions include descriptive ‘as if’ parallels (e.g., child behaves ‘as if’ Alexa was a friend), or normative assumptions that human-human engagements are generally superior to human-technology engagements. Instead, the article reviews different examples from the literature suggesting the nature of anthropomorphism may change as humans’ experiential understandings of humanness change, and this may particularly apply to today’s children as their social cognition develops in interaction with technological entities which are increasingly characterized by unprecedented combinations of human and non-human qualities.
“…Befunde des Länderindikators 2017 verweisen zudem darauf, dass digitale Medien im Unterricht zur selbstständigen Recherche, Aufbereitung und Visualisierung von Unterrichtsinhalten eingesetzt werden können (Eickelmann et al 2017). Zur vertiefenden Auseinandersetzung mit Unterrichtsinhalten werden weiterhin Simulationsprogramme genutzt, welche die Kommunikation über Unterrichtsinhalte zwischen Schülerinnen und Schülern und Algorithmen ermöglichen (Xu et al 2021 (Dubberke et al 2008). Digitale Medien können in diesem Sinne zur Bereitstellung personalisierten Feedbacks (Levy 2009;Ware et al 2012) sowie zum Monitoring des individuellen Lernfortschritts eingesetzt werden (Faber 2020;Hillmayr et al 2017).…”
Section: Unterrichtsqualität Und Digitale Medienunclassified
ZusammenfassungObwohl der Einsatz digitaler Medien in Lehr-Lern-Prozessen zunehmend an Bedeutung gewinnt, befassen sich Studien nur vereinzelt mit der Frage, inwiefern digitale Medien im Unterricht zur Umsetzung von Unterrichtsqualitätsdimensionen genutzt werden. Gleichzeitig ist wenig über die Bedingungsfaktoren einer solchen qualitätsvollen Umsetzung von Unterricht mit digitalen Medien bekannt. Die vorliegende Studie untersucht vor diesem Hintergrund, inwiefern Schulmerkmale vermittelt über Lehrkräftemerkmale dazu beitragen, dass Lehrkräfte digitale Medien nutzen, um im Unterricht zu strukturieren, kognitiv zu aktivieren, konstruktiv zu unterstützen sowie zu individualisieren. Ausgewertet wurden Daten von 280 Lehrkräften an Schulen der Sekundarstufe in Deutschland (52,1 % weiblich, Alter: M = 43,88, SD = 10,00). Die Ergebnisse des Strukturgleichungsmodells verweisen darauf, dass die Zufriedenheit mit der schulischen Unterstützung zum Einsatz digitaler Medien vermittelt über die digitalen (berufsunabhängigen) Kompetenzselbsteinschätzungen in positivem Zusammenhang mit der Nutzung digitaler Medien zum Zwecke der Individualisierung, kognitiven Aktivierung und konstruktiven Unterstützung im Unterricht steht. Die von Lehrkräften berichtete vielfältige technische Schulausstattung sowie die berichteten positiven Wertüberzeugungen in Bezug auf den Einsatz digitaler Medien im Unterricht sind direkt positiv mit der Nutzung digitaler Medien zur Umsetzung der Unterrichtsqualitätsdimensionen assoziiert.
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