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1. Towards Embodied Wearable Intelligent Tutoring Systems

   Rasul, I. (April 2023, Lecture notes in computer science)

   Frasson, C. (Ed.)

   Embodied cognition posits that human-environment interac- tion positively impacts thinking and learning, making it a valuable ped- agogical tool. Technology in teaching and learning has seen tremendous maturation, such as the development of Intelligent Tutoring Systems (ITS). However, most ITS provide static learning experiences that do not incorporate embodiment, movement, and interaction with the space around the learner. This paper examines the results of using an embod- ied tutoring system across three case studies with different dimensions of embodiment. In all cases, we found trends highlighting how embodied tutoring systems can support learning. We also discuss different ways to incorporate embodiment into future research on ITS. 

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2. Towards Embodied Wearable Intelligent Tutoring Systems

   Rasul, I. (April 2023, Lecture notes in computer science)

   Embodied cognition posits that human-environment interaction positively impacts thinking and learning, making it a valuable pedagogical tool. Technology in teaching and learning has seen tremendous maturation, such as the development of Intelligent Tutoring Systems (ITS). However, most ITS provide static learning experiences that do not incorporate embodiment, movement, and interaction with the space around the learner. This paper examines the results of using an embodied tutoring system across three case studies with different dimensions of embodiment. In all cases, we found trends highlighting how embodied tutoring systems can support learning. We also discuss different ways to incorporate embodiment into future research on ITS. 

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3. Improving Mathematics Tutoring With A Code Scratchpad

   https://doi.org/10.18653/v1/2023.bea-1.2  

   Upadhyay, Shriyash; Ginsberg, Etan; Callison-Burch, Chris (July 2023, Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023))

   Large language models can solve reasoning tasks (like math problems) more effectively when they are allowed to generate rationales. However, a good tutoring system should not just generate solutions, but should also generate explanations and should be able to correct and guide students. We show that providing a code scratchpad improves performance on each tutoring step with a gradeschool mathematics dataset. On these tutoring tasks, GPT-3 models provided with a code scratchpad significantly outperform those given only a language scratchpad (77.7% vs 48.7% cumulative accuracy). 

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4. Toward Personalizing Students' Education with Crowdsourced Tutoring

   https://doi.org/10.1145/3430895.3460130  

   Prihar, Ethan; Patikorn, Thanaporn; Botelho, Anthony; Sales, Adam; Heffernan, Neil (June 2021, Lerning @ Scale 2021)

   null (Ed.)

   A s m or e e d u c at or s i nt e gr at e t h eir c urri c ul a wit h o nli n e l e ar ni n g, it i s e a si er t o cr o w d s o ur c e c o nt e nt fr o m t h e m. Cr o w ds o ur c e d t ut ori n g h a s b e e n pr o v e n t o r eli a bl y i n cr e a s e st u d e nt s’ n e xt pr o bl e m c orr e ct n e s s. I n t hi s w or k, w e c o n fir m e d t h e fi n di n g s of a pr e vi o u s st u d y i n t hi s ar e a, wit h str o n g er c o n fi d e n c e m ar gi n s t h a n pr e vi o u sl y, a n d r e v e al e d t h at o nl y a p orti o n of cr o w d s o ur c e d c o nt e nt cr e at or s h a d a r eli a bl e b e n e fit t o st ud e nt s. F urt h er m or e, t hi s w or k pr o vi d e s a m et h o d t o r a n k c o nt e nt cr e at or s r el ati v e t o e a c h ot h er, w hi c h w a s u s e d t o d et er mi n e w hi c h c o nt e nt cr e at or s w er e m o st eff e cti v e o v er all, a n d w hi c h c o nt e nt cr e at or s w er e m o st eff e cti v e f or s p e ci fi c gr o u p s of st u d e nt s. W h e n e x pl ori n g d at a fr o m Te a c h er A SSI S T, a f e at ur e wit hi n t h e A S SI S T m e nt s l e ar ni n g pl atf or m t h at cr o w d s o ur c e s t ut ori n g fr o m t e a c h er s, w e f o u n d t h at w hil e o v erall t hi s pr o gr a m pr o vi d e s a b e n e fit t o st u d e nt s, s o m e t e a c h er s cr e at e d m or e eff e cti v e c o nt e nt t h a n ot h er s. D e s pit e t hi s fi n di n g, w e di d n ot fi n d e vi d e n c e t h at t h e eff e cti v e n e s s of c o nt e nt r eli a bl y v ari e d b y st u d e nt k n o wl e d g e-l e v el, s u g g e sti n g t h at t h e c o nt e nt i s u nli k el y s uit a bl e f or p er s o n ali zi n g i n str u cti o n b a s e d o n st u d e nt k n o wl e d g e al o n e. T h e s e fi n di n g s ar e pr o mi si n g f or t h e f ut ur e of cr o w d s o ur c e d t ut ori n g a s t h e y h el p pr o vi d e a f o u n d ati o n f or a s s e s si n g t h e q u alit y of cr o w d s o ur c e d c o nt e nt a n d i n v e sti g ati n g c o nt e nt f or o p p ort u niti e s t o p er s o n ali z e st u d e nt s’ e d u c ati o n. 

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5. Classroom Evaluation of a Gamified Adaptive Tutoring System

   https://doi.org/10.1109/FIE56618.2022.9962718  

   Tang, Ying; Hare, Ryan; Ferguson, Sarah (October 2022, 2022 IEEE Frontiers in Education Conference)