{"title":"通过对话聊天机器人和数字内容吸引学生:气候行动的视角","authors":"T. Menkhoff, B. Gan","doi":"10.54941/ahfe1002960","DOIUrl":null,"url":null,"abstract":"In this case study, we report experiences deploying a conversational chatbot as a\n pre-class and post-class engagement tool for undergraduate students enrolled in\n sustainability-related courses aimed at educating them about the severity of climate\n change and the importance of climate action by offsetting one’s carbon footprint (e.g,\n by planting trees or mangroves in SEA). The intitiative supports the university’s\n sustainability efforts in general and our new sustainability major in particular aimed\n at helping students to achieve sustainability-related learning outcomes with reference\n to climate change and climate action (SDG 13), one of the 17 Sustainable Development\n Goals established by the United Nations in 2015.Climate action means stepped-up efforts\n to reduce greenhouse gas emissions and strengthen resilience and adaptive capacity to\n climate-induced impacts, including: climate-related hazards in all countries;\n integrating climate change measures into national policies, strategies and planning; and\n improving education, awareness-raising and human and institutional capacity with respect\n to climate change mitigation, adaptation, impact reduction and early warning…\n (https://www.sdfinance.undp.org/content/sdfinance/en/home/sdg/goal-13--climate-action.html).Related\n teaching and learning challenges we have observed in our classes include climate change\n ignorance / indifference, lack of confidence in calculating one’s own carbon footprint,\n not knowing why personal climate action is important and how it can contribute to active\n decarbonisation etc. to mitigate climate change. Several research studies have\n underlined the potentially positive effect of Chatbots on students’ learning in\n educational institutions ranging from primary schools to IHLs. “Conveniency”,\n “satisfaction”, “engagement” and “motivation” have been highlighted in previous studies\n as benefits of using conversational pedagogical agents (= “Chatbots”) in teaching and\n learning (Smutny & Schreiberova, 2020; Martha & Santoso, 2019; Satow, 2017;\n Fadhill & Villaforita, 2017; Pereira, 2016; Kim & Baylor, 2007).Conceptually,\n the ongoing project relates to the study of technology-mediated learning in general and\n chatbot-mediated learning in particular Winkler & Söllner (2018) have highlighted\n the advantages of chatbot-mediated learning (CML) in educational settings with regard to\n positive learning outcomes that include learning success and student satisfaction.\n Chatbot-mediated learning (CML) has enabled learners to take on a proactive approach in\n creating an individualized learning experience in the context of large-scale lectures\n and massive open online courses (MOOC) where individualized support was lacking.\n Chatbots play an essential role in T&L by supporting teachers to create interactive\n learning experience when teachers are not physically present, monitoring results and\n performance, and disseminating regular reminders to check on homework and encourage\n students in their learning efforts (Clarizia et al, 2018). Research also observed that\n the use of chatbots helped to facilitate better communication and interaction between\n students and teachers as well as amongst students (Clarizia et al., 2018; Tamayo et al.,\n 2020). CML also helped to bridge the gap in distance learning by assisting students\n during the revising process during time away from school (Tamayo et al., 2020).A key\n intent of the ongoing project is to build a chatbot that can effectively educate and\n engage students with regard to the concept of ‘carbon footprint’ (which refers to the\n total amount of greenhouse gases such as carbon dioxide and methane that are generated\n by our actions) and to make them appreciate the importance of reducing one’s own carbon\n emissions (= footprint) to avoid a 2℃ rise in global temperatures and to (actively)\n combat climate change.By using Google’s DialogFlow as brain (and T&L tool) of the\n chatbot, we argue that bot building workshops integrated into a learning course do act\n as a teaser for learners to review and internalise relevant climate change and carbon\n footprint related learning content (e.g., by using relevant personas/avatars such as The\n Doubtful Debbie, The Alarmed Ali, The Concerned Chris, The Disengaged Devi etc),\n enabling students to appreciate the urgency of concrete offsetting opportunities\n provided by new tech start-ups such as Handprint. Bots can also feature topic-related\n learning tests in support of relevant learning outcomes.","PeriodicalId":383834,"journal":{"name":"Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial\n Intelligence and Future Applications","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Engaging Students through Conversational Chatbots and Digital Content: A Climate\\n Action Perspective\",\"authors\":\"T. Menkhoff, B. Gan\",\"doi\":\"10.54941/ahfe1002960\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this case study, we report experiences deploying a conversational chatbot as a\\n pre-class and post-class engagement tool for undergraduate students enrolled in\\n sustainability-related courses aimed at educating them about the severity of climate\\n change and the importance of climate action by offsetting one’s carbon footprint (e.g,\\n by planting trees or mangroves in SEA). The intitiative supports the university’s\\n sustainability efforts in general and our new sustainability major in particular aimed\\n at helping students to achieve sustainability-related learning outcomes with reference\\n to climate change and climate action (SDG 13), one of the 17 Sustainable Development\\n Goals established by the United Nations in 2015.Climate action means stepped-up efforts\\n to reduce greenhouse gas emissions and strengthen resilience and adaptive capacity to\\n climate-induced impacts, including: climate-related hazards in all countries;\\n integrating climate change measures into national policies, strategies and planning; and\\n improving education, awareness-raising and human and institutional capacity with respect\\n to climate change mitigation, adaptation, impact reduction and early warning…\\n (https://www.sdfinance.undp.org/content/sdfinance/en/home/sdg/goal-13--climate-action.html).Related\\n teaching and learning challenges we have observed in our classes include climate change\\n ignorance / indifference, lack of confidence in calculating one’s own carbon footprint,\\n not knowing why personal climate action is important and how it can contribute to active\\n decarbonisation etc. to mitigate climate change. Several research studies have\\n underlined the potentially positive effect of Chatbots on students’ learning in\\n educational institutions ranging from primary schools to IHLs. “Conveniency”,\\n “satisfaction”, “engagement” and “motivation” have been highlighted in previous studies\\n as benefits of using conversational pedagogical agents (= “Chatbots”) in teaching and\\n learning (Smutny & Schreiberova, 2020; Martha & Santoso, 2019; Satow, 2017;\\n Fadhill & Villaforita, 2017; Pereira, 2016; Kim & Baylor, 2007).Conceptually,\\n the ongoing project relates to the study of technology-mediated learning in general and\\n chatbot-mediated learning in particular Winkler & Söllner (2018) have highlighted\\n the advantages of chatbot-mediated learning (CML) in educational settings with regard to\\n positive learning outcomes that include learning success and student satisfaction.\\n Chatbot-mediated learning (CML) has enabled learners to take on a proactive approach in\\n creating an individualized learning experience in the context of large-scale lectures\\n and massive open online courses (MOOC) where individualized support was lacking.\\n Chatbots play an essential role in T&L by supporting teachers to create interactive\\n learning experience when teachers are not physically present, monitoring results and\\n performance, and disseminating regular reminders to check on homework and encourage\\n students in their learning efforts (Clarizia et al, 2018). Research also observed that\\n the use of chatbots helped to facilitate better communication and interaction between\\n students and teachers as well as amongst students (Clarizia et al., 2018; Tamayo et al.,\\n 2020). CML also helped to bridge the gap in distance learning by assisting students\\n during the revising process during time away from school (Tamayo et al., 2020).A key\\n intent of the ongoing project is to build a chatbot that can effectively educate and\\n engage students with regard to the concept of ‘carbon footprint’ (which refers to the\\n total amount of greenhouse gases such as carbon dioxide and methane that are generated\\n by our actions) and to make them appreciate the importance of reducing one’s own carbon\\n emissions (= footprint) to avoid a 2℃ rise in global temperatures and to (actively)\\n combat climate change.By using Google’s DialogFlow as brain (and T&L tool) of the\\n chatbot, we argue that bot building workshops integrated into a learning course do act\\n as a teaser for learners to review and internalise relevant climate change and carbon\\n footprint related learning content (e.g., by using relevant personas/avatars such as The\\n Doubtful Debbie, The Alarmed Ali, The Concerned Chris, The Disengaged Devi etc),\\n enabling students to appreciate the urgency of concrete offsetting opportunities\\n provided by new tech start-ups such as Handprint. 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Engaging Students through Conversational Chatbots and Digital Content: A Climate
Action Perspective
In this case study, we report experiences deploying a conversational chatbot as a
pre-class and post-class engagement tool for undergraduate students enrolled in
sustainability-related courses aimed at educating them about the severity of climate
change and the importance of climate action by offsetting one’s carbon footprint (e.g,
by planting trees or mangroves in SEA). The intitiative supports the university’s
sustainability efforts in general and our new sustainability major in particular aimed
at helping students to achieve sustainability-related learning outcomes with reference
to climate change and climate action (SDG 13), one of the 17 Sustainable Development
Goals established by the United Nations in 2015.Climate action means stepped-up efforts
to reduce greenhouse gas emissions and strengthen resilience and adaptive capacity to
climate-induced impacts, including: climate-related hazards in all countries;
integrating climate change measures into national policies, strategies and planning; and
improving education, awareness-raising and human and institutional capacity with respect
to climate change mitigation, adaptation, impact reduction and early warning…
(https://www.sdfinance.undp.org/content/sdfinance/en/home/sdg/goal-13--climate-action.html).Related
teaching and learning challenges we have observed in our classes include climate change
ignorance / indifference, lack of confidence in calculating one’s own carbon footprint,
not knowing why personal climate action is important and how it can contribute to active
decarbonisation etc. to mitigate climate change. Several research studies have
underlined the potentially positive effect of Chatbots on students’ learning in
educational institutions ranging from primary schools to IHLs. “Conveniency”,
“satisfaction”, “engagement” and “motivation” have been highlighted in previous studies
as benefits of using conversational pedagogical agents (= “Chatbots”) in teaching and
learning (Smutny & Schreiberova, 2020; Martha & Santoso, 2019; Satow, 2017;
Fadhill & Villaforita, 2017; Pereira, 2016; Kim & Baylor, 2007).Conceptually,
the ongoing project relates to the study of technology-mediated learning in general and
chatbot-mediated learning in particular Winkler & Söllner (2018) have highlighted
the advantages of chatbot-mediated learning (CML) in educational settings with regard to
positive learning outcomes that include learning success and student satisfaction.
Chatbot-mediated learning (CML) has enabled learners to take on a proactive approach in
creating an individualized learning experience in the context of large-scale lectures
and massive open online courses (MOOC) where individualized support was lacking.
Chatbots play an essential role in T&L by supporting teachers to create interactive
learning experience when teachers are not physically present, monitoring results and
performance, and disseminating regular reminders to check on homework and encourage
students in their learning efforts (Clarizia et al, 2018). Research also observed that
the use of chatbots helped to facilitate better communication and interaction between
students and teachers as well as amongst students (Clarizia et al., 2018; Tamayo et al.,
2020). CML also helped to bridge the gap in distance learning by assisting students
during the revising process during time away from school (Tamayo et al., 2020).A key
intent of the ongoing project is to build a chatbot that can effectively educate and
engage students with regard to the concept of ‘carbon footprint’ (which refers to the
total amount of greenhouse gases such as carbon dioxide and methane that are generated
by our actions) and to make them appreciate the importance of reducing one’s own carbon
emissions (= footprint) to avoid a 2℃ rise in global temperatures and to (actively)
combat climate change.By using Google’s DialogFlow as brain (and T&L tool) of the
chatbot, we argue that bot building workshops integrated into a learning course do act
as a teaser for learners to review and internalise relevant climate change and carbon
footprint related learning content (e.g., by using relevant personas/avatars such as The
Doubtful Debbie, The Alarmed Ali, The Concerned Chris, The Disengaged Devi etc),
enabling students to appreciate the urgency of concrete offsetting opportunities
provided by new tech start-ups such as Handprint. Bots can also feature topic-related
learning tests in support of relevant learning outcomes.