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Let's Talk It Out: A Chatbot for Effective Study Habit Behavioral Change

Published: 22 April 2021 Publication History
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  • Abstract

    Research has shown study habits and skills to be correlated with academic success, calling for a deeper comprehension of these behaviors and processes to design effective interventions for struggling students. Chatbots have recently been used as a persuasive technology to help support behavioral change, making them an intriguing design space for students' study habits and skills. This paper investigated the feasibility of using chatbots for promoting behavioral change of college students majoring in Computer Science (CS). We conducted semi-structured interviews with CS peer-tutors and surveyed university freshmen to understand students' study habits and identify technical intervention opportunities. Inspired by the findings, we designed StudyBuddy, a chatbot prototype deployed in Slack that periodically sends tips, provides assessments of students' study habits via surveys, helps the students break down assignments, recommends academic resources, and sends reminders. We evaluated the usability of the prototype in-depth with 8 students (both first-year and senior students) and 5 course instructors followed by a large scale evaluative survey (n=117) using video of the prototype. Our research identified important design challenges such as building trust and preserving privacy, limiting interaction costs, and supporting both immediate and long-term sustainable support. Likewise, we proposed design recommendations that demonstrate context awareness, personalize the experience based on user preferences, and adapt over time as students mature and grow.

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    [1]
    RV Belfin, AJ Shobana, Megha Manilal, Ashly Ann Mathew, and Blessy Babu. 2019. A Graph Based Chatbot for Cancer Patients. In 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS). IEEE, Coimbature,India, 717--721.
    [2]
    Mordechai Ben-Ari. 2004. Situated Learning in Computer Science Education. Computer Science Education, Vol. 14, 2 (2004), 85--100.
    [3]
    Sylvia Beyer. 2014. Why Are Women Underrepresented in Computer Science? Gender Differences in Stereotypes, Self-Efficacy, Values, and Interests and Predictors of Future CS Course-Taking and Grades. Computer Science Education, Vol. 24, 2--3 (2014), 153--192. https://doi.org/10.1080/08993408.2014.963363
    [4]
    Sylvia Beyer, Kristina Rynes, Julie Perrault, Kelly Hay, and Susan Haller. 2003. Gender Differences in Computer Science Students. In Proceedings of the 34th SIGCSE technical symposium on Computer science education (SIGCSE '03). Association for Computing Machinery, New York, NY, USA, 49--53. https://doi.org/10.1145/611892.611930
    [5]
    Davide Calvaresi, Jean-Paul Calbimonte, Fabien Dubosson, Amro Najjar, and Michael Schumacher. 2019. Social Network Chatbots for Smoking Cessation: Agent and Multi-Agent Frameworks. In 2019 IEEE/WIC/ACM International Conference on Web Intelligence. IEEE, Thessaloniki, Greece, 286--292.
    [6]
    Sandra Beermann Chacko and Mary E Huba. 1991. Validation of the Learning and Study Strategies Inventory With a Sample of Students in Nursing. NACADA Journal, Vol. 11, 2 (1991), 5--13.
    [7]
    S Chamundeswari, V Sridevi, and Archana Kumari. 2014. Self-Concept, Study Habit and Academic Achievement of Students. International Journal of Humanities Social Sciences and Education, Vol. 1, 10 (2014), 47--55.
    [8]
    Cheng-Min Chao. 2019. Factors Determining the Behavioral Intention to Use Mobile Learning: An Application and Extension of the UTAUT Model. Frontiers in Psychology, Vol. 10 (2019). https://doi.org/10.3389/fpsyg.2019.01652 Publisher: Frontiers.
    [9]
    Marcia Roe Clark. 2005. Negotiating the Freshman Year: Challenges and Strategies among First-Year College Students. Journal of College Student Development, Vol. 46, 3 (2005), 296--316.
    [10]
    James Clawson, Jessica A. Pater, Andrew D. Miller, Elizabeth D. Mynatt, and Lena Mamykina. 2015. No Longer Wearing: Investigating the Abandonment of Personal Health-Tracking Technologies on Craigslist. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. 647--658.
    [11]
    Emerson Collective. 2020. Supporting Students During COVID-19: Resources for Remote Learning. https://www.emersoncollective.com/covid19-resources-for-remote-learning Retrieved May 31, 2020 from
    [12]
    Alexandre Coninx, Paul Baxter, Elettra Oleari, Sara Bellini, Bert Bierman, Olivier Blanson Henkemans, Lola Ca namero, Piero Cosi, Valentin Enescu, Raquel Ros Espinoza, et almbox. 2016. Towards Long-Term Social child-robot Interaction: Using Multi-Activity Switching to Engage Young Users. Journal of Human-Robot Interaction, Vol. 5, 1 (2016), 32--67.
    [13]
    Sunny Consolvo, David W. McDonald, and James A. Landay. 2009. Theory-Driven Design Strategies for Technologies that Support Behavior Change in Everyday Life. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '09). Association for Computing Machinery, Boston, MA, USA, 405--414. https://doi.org/10.1145/1518701.1518766
    [14]
    National Science and Technology Council. 2018. Charting a Course for Success: America's Strategy for STEM Education. Technical Report. Office of Science and Technology Policy Washington, DC.
    [15]
    Marcus Credé and Nathan R. Kuncel. 2008. Study Habits, Skills, and Attitudes: The Third Pillar Supporting Collegiate Academic Performance. Perspectives on Psychological Science, Vol. 3, 6 (Nov. 2008), 425--453. https://doi.org/10.1111/j.1745--6924.2008.00089.x
    [16]
    Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-Training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805 (2018).
    [17]
    Mateusz Dolata and Gerhard Schwabe. 2018. Don't be Afraid! Persuasive Practices in the Wild. Computer Supported Cooperative Work, Vol. 27, 3 (Dec. 2018), 427--462. https://doi.org/10.1007/s10606-018-9330-4
    [18]
    Benedict Du Boulay, Katerina Avramides, Rosemary Luckin, Erika Mart'inez-Mirón, Genaro Rebolledo Méndez, and Amanda Carr. 2010. Towards Systems that Care: a Conceptual Framework based on Motivation, Metacognition and Affect. International Journal of Artificial Intelligence in Education, Vol. 20, 3 (2010), 197--229.
    [19]
    Teresa Garcia Duncan and Wilbert J McKeachie. 2005. The Making of the Motivated Strategies for Learning Questionnaire. Educational Psychologist, Vol. 40, 2 (2005), 117--128.
    [20]
    Andrew Emerson, Fernando J. Rodr'iguez, Bradford Mott, Andy Smith, Wookhee Min, Kristy Elizabeth Boyer, Cody Smith, Eric Wiebe, and James Lester. 2019. Predicting Early and Often: Predictive Student Modeling for Block-Based Programming Environments. In Proceedings of The 12th International Conference on Educational Data Mining (EDM 2019), Vol. 39. ERIC, 48.
    [21]
    Johna Faulconer, Jayne Geissler, Diane Majewski, and John Trifilo. 2014. Adoption of an Early-Alert System to Support University Student Success. Delta Kappa Gamma Bulletin, Vol. 80, 2 (2014).
    [22]
    Justin Filippou, Christopher Cheong, and France Cheong. 2016. Combining The Fogg Behavioural Model And Hook Model To Design Features In A Persuasive App To Improve Study Habits. arXiv preprint arXiv:1606.03531 (2016).
    [23]
    Brian J Fogg. 2002. Persuasive technology: using computers to change what we think and do. Ubiquity, Vol. 2002, December (2002), 2.
    [24]
    Brian J Fogg. 2009. A behavior model for persuasive design. In Proceedings of the 4th international Conference on Persuasive Technology. 1--7.
    [25]
    Ashok Goel, Brian Creeden, Mithun Kumble, Shanu Salunke, Abhinaya Shetty, and Bryan Wiltgen. 2015. Using Watson for Enhancing Human-Computer Co-Creativity. In 2015 AAAI Fall Symposium Series. AAAI 2015 Fall Symposium, Arlington, Virginia, 22--29.
    [26]
    Philip J Guo. 2013. Online Python Tutor: Embeddable Web-Based Program Visualization for CS Education. In Proceeding of the 44th ACM technical symposium on Computer science education. 579--584.
    [27]
    Olivier A Blanson Henkemans, Bert PB Bierman, Joris Janssen, Mark A Neerincx, Rosemarijn Looije, Hanneke van der Bosch, and Jeanine AM van der Giessen. 2013. Using a Robot to Personalise Health Education for Children with Diabetes Type 1: A Pilot Study. Patient education and counseling, Vol. 92, 2 (2013), 174--181.
    [28]
    Carmen Holotescu. 2016. MOOCBuddy: a Chatbot for Personalized Learning with MOOCs. In RoCHI. RoCHI, Iasi, Romania, 91--94.
    [29]
    Chin-Yuan Huang, Ming-Chin Yang, Chin-Yu Huang, Yu-Jui Chen, Meng-Lin Wu, and Kai-Wen Chen. 2018. A Chatbot-supported Smart Wireless Interactive Healthcare System for Weight Control and Health Promotion. In 2018 IEEE International Conference on Industrial Engineering and Engineering Management. IEEE, Bangkok, 1791--1795.
    [30]
    Sandeep M. Jayaprakash, Erik W. Moody, Eitel J. M. Lauría, James R. Regan, and Joshua D. Baron. 2014. Early Alert of Academically At-Risk Students: An Open Source Analytics Initiative. Journal of Learning Analytics, Vol. 1, 1 (May 2014). https://doi.org/10.18608/jla.2014.11.3
    [31]
    Dipesh Kadariya, Revathy Venkataramanan, Hong Yung Yip, Maninder Kalra, Krishnaprasad Thirunarayanan, and Amit Sheth. 2019. kBot: Knowledge-enabled Personalized Chatbot for Asthma Self-Management. In 2019 IEEE International Conference on Smart Computing. IEEE, Washington, DC, USA, 138--143.
    [32]
    Takayuki Kanda, Takayuki Hirano, Daniel Eaton, and Hiroshi Ishiguro. 2004. Interactive Robots as Social Partners and Peer Tutors for Children: A Field Trial. Human-Computer Interaction, Vol. 19, 1--2 (2004), 61--84.
    [33]
    Saskia M. Kelders, Robin N. Kok, Hans C. Ossebaard, and Julia EWC Van Gemert-Pijnen. 2012. Persuasive System Design Does Matter: A Systematic Review of Adherence to Web-Based Interventions. Journal of Medical Internet Research, Vol. 14, 6 (2012). https://doi.org/10.2196/jmir.2104
    [34]
    Juho Kim, Philip J Guo, Daniel T Seaton, Piotr Mitros, Krzysztof Z Gajos, and Robert C Miller. 2014. Understanding In-Video Dropouts and Interaction Peaks in Online Lecture Videos. In Proceedings of the first ACM conference on Learning@Scale. 31--40.
    [35]
    Rafal Kocielnik, Daniel Avrahami, Jennifer Marlow, Di Lu, and Gary Hsieh. 2018. Designing for Workplace Reflection: A Chat and Voice-Based Conversational Agent. In Proceedings of the 2018 Designing Interactive Systems Conference (Hong Kong, China) (DIS '18). Association for Computing Machinery, New York, NY, USA, 881--894. https://doi.org/10.1145/3196709.3196784
    [36]
    Ilya Kreynin, MohammedShabbar Manek, and Chirag Variawa. 2019. Creating a Virtual Chatbot to Scaffold Skills Development in First-Year Engineering Education. Proceedings of the Canadian Engineering Education Association (CEEA) (2019).
    [37]
    Nicholas D Lane, Sourav Bhattacharya, Petko Georgiev, Claudio Forlivesi, and Fahim Kawsar. 2015. An Early Resource Characterization of Deep Learning on Wearables, Smartphones and Internet-of-Things Devices. In Proceedings of the 2015 international workshop on internet of things towards applications. 7--12.
    [38]
    Randy A LaRose. 2009. The Relationship between Religiosity and Educational Pursuit and Perception. All Graduate Theses and Dissertations (2009).
    [39]
    Amanda Lazar, Christian Koehler, Joshua Tanenbaum, and David H. Nguyen. 2015. Why We Use and Abandon Smart Devices. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '15). ACM, New York, NY, USA, 635--646. https://doi.org/10.1145/2750858.2804288 event-place: Osaka, Japan.
    [40]
    Dan Ledger and Daniel McCaffrey. 2014. Inside Wearables Part 1: How Behavior Change Unlocks Long-Term Engagement. (2014). https://medium.com/@endeavourprtnrs/inside-wearable-how-the-science-of-human-behavior-change-offers-the-secret-to-long-term-engagement-a15b3c7d4cf3
    [41]
    Iolanda Leite, Ginevra Castellano, André Pereira, Carlos Martinho, and Ana Paiva. 2014. Empathic Robots for Long-Term Interaction. International Journal of Social Robotics, Vol. 6, 3 (2014), 329--341.
    [42]
    Kai Lukoff, Taoxi Li, Yuan Zhuang, and Brian Y Lim. 2018. TableChat: Mobile Food Journaling to Facilitate Family Support for Healthy Eating. Proceedings of the ACM on Human-Computer Interaction, Vol. 2, CSCW (2018), 1--28.
    [43]
    Carol Maher, Jillian Ryan, Christina Ambrosi, and Sarah Edney. 2017. Users' Experiences of Wearable Activity Trackers: a Cross-Sectional Study. BMC public health, Vol. 17, 1 (2017), 880.
    [44]
    John Matthews, Khin Than Win, Harri Oinas-Kukkonen, and Mark Freeman. 2016. Persuasive Technology in Mobile Applications Promoting Physical Activity: a Systematic Review. Journal of Medical Systems, Vol. 40, 3 (Jan. 2016), 72. https://doi.org/10.1007/s10916-015-0425-x
    [45]
    Joel McFarland, Bill Hussar, Jijun Zhang, Xiaolei Wang, Ke Wang, Sarah Hein, Melissa Diliberti, Emily Forrest Cataldi, Farrah Bullock Mann, and Amy Barmer. 2019. The Condition of Education 2019. NCES 2019--144. National Center for Education Statistics (2019).
    [46]
    Carolina Mega, Lucia Ronconi, and Rossana De Beni. 2014. What Makes a Good Student? How Emotions, Self-Regulated Learning, and Motivation Contribute to Academic Achievement. Journal of educational psychology, Vol. 106, 1 (2014), 121.
    [47]
    Joseph E Michaelis and Bilge Mutlu. 2019. Supporting Interest in Science Learning with a Social Robot. In Proceedings of the 18th ACM International Conference on Interaction Design and Children. ACM, 71--82.
    [48]
    Vivian Genaro Motti and Kelly Caine. 2016. Smart Wearables or Dumb Wearables? Understanding How Context Impacts the UX in Wrist Worn Interaction. In Proceedings of the 34th ACM International Conference on the Design of Communication. 1--10.
    [49]
    Dina Fitria Murad, Adhi Gustian Iskandar, Erick Fernando, Tica Shinta Octavia, and Deryan Everestha Maured. 2019. Towards Smart LMS to Improve Learning Outcomes Students Using LenoBot with Natural Language Processing. In 2019 6th International Conference on Information Technology, Computer and Electrical Engineering. IEEE, Semarang, Indonesia, 1--6.
    [50]
    Seyed Mehdi Nasehi, Jonathan Sillito, Frank Maurer, and Chris Burns. 2012. What Makes a Good Code Example?: A Study of Programming Q&A in StackOverflow. In 2012 28th IEEE International Conference on Software Maintenance (ICSM). IEEE, 25--34.
    [51]
    Kyo-Joong Oh, Dongkun Lee, Byungsoo Ko, and Ho-Jin Choi. 2017. A Chatbot for Psychiatric Counseling in Mental Healthcare Service based on Emotional Dialogue Analysis and Sentence Generation. In 2017 18th IEEE International Conference on Mobile Data Management. IEEE, Daejeon, South Korea, 371--375.
    [52]
    Rita Orji and Karyn Moffatt. 2018. Persuasive Technology for Health and Wellness: State-of-the-art and emerging trends. Health Informatics Journal, Vol. 24, 1 (March 2018). https://doi.org/10.1177/1460458216650979
    [53]
    Stephen Purpura, Victoria Schwanda, Kaiton Williams, William Stubler, and Phoebe Sengers. 2011. Fit4life: The Design of a Persuasive Technology Promoting Healthy Behavior and Ideal Weight. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '11). Association for Computing Machinery, Vancouver, BC, Canada, 423--432. https://doi.org/10.1145/1978942.1979003
    [54]
    Yizhou Qian and James Lehman. 2017. Students' Misconceptions and Other difficulties in Introductory Programming: A Literature Review. ACM Transactions on Computing Education (TOCE), Vol. 18, 1 (2017), 1--24.
    [55]
    Steven R. Rick, Aaron Paul Goldberg, and Nadir Weibel. 2019. SleepBot: Encouraging Sleep Hygiene Using an Intelligent Chatbot. In Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion (Marina del Ray, California) (IUI '19). Association for Computing Machinery, New York, NY, USA, 107--108. https://doi.org/10.1145/3308557.3308712
    [56]
    Pooja Sankar, Jessica Gilmartin, and Melissa Sobel. 2015. An Examination of Belongingness and Confidence among Female Computer Science Students. ACM SIGCAS Computers and Society, Vol. 45, 2 (July 2015), 7--10. https://doi.org/10.1145/2809957.2809960
    [57]
    Jill M. Simons. 2011. A National Study of Student Early Alert Models at Four-Year Institutions of Higher Education. Ed.D. Arkansas State University, United States -- Arkansas. http://search.proquest.com/docview/910327556/abstract/97BE5A6AF7BB47B2PQ/1
    [58]
    Dale R. Tampke. 2013. Developing, implementing, and assessing an early alert system. Journal of College Student Retention: Research, Theory & Practice, Vol. 14, 4 (2013).
    [59]
    Oriol Vinyals and Quoc Le. 2015. A neural conversational model. arXiv preprint arXiv:1506.05869 (2015).
    [60]
    Yi-Shun Wang, Ming-Cheng Wu, and Hsiu-Yuan Wang. 2009. Investigating the Determinants and Age and Gender Differences in the Acceptance of Mobile Learning. British Journal of Educational Technology, Vol. 40, 1 (Jan. 2009), 92--118. https://doi.org/10.1111/j.1467--8535.2007.00809.x
    [61]
    Claire E Weinstein, D Palmer, and Ann C Schulte. 1987. Learning And Study Strategies Inventory (LASSI). Clearwater, FL: H & H Publishing (1987).
    [62]
    Jacqueline M Kory Westlund, Hae Won Park, Randi Williams, and Cynthia Breazeal. 2018. Measuring Young Children's Long-Term Relationships with Social Robots. In Proceedings of the 17th ACM conference on interaction design and children. 207--218.
    [63]
    Alex C. Williams, Harmanpreet Kaur, Gloria Mark, Anne Loomis Thompson, Shamsi T. Iqbal, and Jaime Teevan. 2018. Supporting Workplace Detachment and Reattachment with Conversational Intelligence. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI '18). Association for Computing Machinery, New York, NY, USA, 1--13. https://doi.org/10.1145/3173574.3173662
    [64]
    Barry J Zimmerman. 1990. Self-Regulating Academic Learning and Achievement: The Emergence of a Social cognitive Perspective. Educational psychology review, Vol. 2, 2 (1990), 173--201.
    [65]
    K Zvereva, V Deviatkov, E Smirnova, and E Manyashev. 2020. Method Of The Student's Motivation Assessment Using Smart Chatbot. In INTED2020 Proceedings. IATED, Valencia,Spain, 627--633.

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      cover image Proceedings of the ACM on Human-Computer Interaction
      Proceedings of the ACM on Human-Computer Interaction  Volume 5, Issue CSCW1
      CSCW
      April 2021
      5016 pages
      EISSN:2573-0142
      DOI:10.1145/3460939
      Issue’s Table of Contents
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      Published: 22 April 2021
      Published in PACMHCI Volume 5, Issue CSCW1

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      Author Tags

      1. behavioral change
      2. chatbot
      3. computer science
      4. persuasive technology
      5. study habits and skills

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