[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.1145/3576050.3576100acmotherconferencesArticle/Chapter ViewAbstractPublication PageslakConference Proceedingsconference-collections
research-article

Using Teacher Dashboards to Customize Lesson Plans for a Problem-Based, Middle School STEM Curriculum

Published: 13 March 2023 Publication History

Abstract

Keeping K-12 teachers engaged during students’ learning and problem solving in technology-enhanced, integrated problem-based learning (PBL) has been shown to support deeper student involvement, and, therefore, better success learning difficult science, computing, and engineering concepts and practices. However, students’ learning processes and corresponding difficulties are not easily noticed by teachers as students learn from these environments as processes are captured through mouse clicks, drag and drop actions, and other low-level activities. As such, teachers find it difficult to set up meaningful interactions with students while also maintaining the focus on student-centered learning. Little research has examined dashboard-supported responsive teaching practices for K-12 PBL. This study examined 8 teachers as they used a co-designed teacher dashboard to assess and respond to students’ learning and strategies during an integrated, PBL STEM curriculum. Teachers completed a series of 5 “planning period simulations” leveraging the dashboard and think-aloud protocols were implemented, supported by semi-structured interview questions, to enable the teachers to verbalize their thought and evaluation processes. Content analysis and epistemic network analysis were conducted to analyze the simulations. Understanding how teachers use dashboards to support evidence-based teaching practices during technology-enhanced curricula is critical for improving teacher support and preparation.

References

[1]
June Ahn, Ha Nguyen, and Fabio Campos. 2021. From Visible to Understandable: Designing for Teacher Agency in Education Data Visualizations. Contemporary Issues in Technology and Teacher Education (2021).
[2]
Shaaron Ainsworth. 2006. DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction 16, 3 (2006), 183–198. https://doi.org/10.1016/j.learninstruc.2006.03.001
[3]
Gregory Benoit, Rachel Slama, Roya Madoff Moussapour, Justin Reich, and Nancy Anderson. 2021. Simulating more equitable discussions: using teacher moments and practice based teacher education in mathematical professional learning. https://open.bu.edu/handle/2144/44488
[4]
Stefania Bocconi, Augusto Chioccariello, Giuliana Dettori, Anusca Ferrari, Katja Engelhardt, Panagiotis Kampylis, and Yves Punie. 2016. Developing Computational Thinking in Compulsory Education - Implications for policy and practice. Technical Report.
[5]
Denise Bressler, Alec Bodzin, Brendan Eagan, and Sara Tabatabai. 2019. Using Epistemic Network Analysis to Examine Discourse and Scientific Practice During a Collaborative Game. Journal of Science Education and Technology 28 (10 2019). https://doi.org/10.1007/s10956-019-09786-8
[6]
James P. Bywater, Jennifer L. Chiu, James Hong, and Vidhya Sankaranarayanan. 2019. The Teacher Responding Tool: Scaffolding the teacher practice of responding to student ideas in mathematics classrooms. Computers & Education 139 (2019), 16–30. https://doi.org/10.1016/j.compedu.2019.05.004
[7]
James P Bywater, Mark Floryan, and Jennifer L Chiu. 2021. DiSCS: A New Sequence Segmentation Method for OpenEnded Learning Environments. In International Conference on Artificial Intelligence in Education. Springer.
[8]
Fabio Campos, June Ahn, Daniela K. DiGiacomo, Ha Nguyen, and Maria Hays. 2021. Making Sense of Sensemaking: Understanding How K–12 Teachers and Coaches React to Visual Analytics. Journal of Learning Analytics 8, 3 (2021), 60–80. https://doi.org/10.18608/jla.2021.7113
[9]
Elizabeth Charters. 2003. The Use of Think-aloud Methods in Qualitative Research An Introduction to Think-aloud Methods. Brock Education Journal 12 (2003).
[10]
Yuxin Chen, Cindy Hmelo-Silver, Susanne Lajoie, Juan Zheng, Lingyun Huang, and Stephen Bodnar. 2021. Using Teacher Dashboards to Assess Group Collaboration in Problem-based Learning. Educational Technology Research and Development 15, 2(2021).
[11]
Janet E. Coffey, David Hammer, Daniel M. Levin, and Terrance Grant. 2011. The missing disciplinary substance of formative assessment. Journal of Research in Science Teaching 48, 10 (2011), 1109–1136. https://doi.org/10.1002/tea.20440
[12]
Andras Csanadi, Brendan R. Eagan, I. Kollar, David Williamson Shaffer, and Frank Fischer. 2018. When coding-and-counting is not enough: using epistemic network analysis (ENA) to analyze verbal data in CSCL research. International Journal of Computer-Supported Collaborative Learning 13 (2018), 419–438.
[13]
Rachel Dickler, Janice Gobert, and Michael Sao Pedro. 2021. Using Innovative Methods to Explore the Potential of an Alerting Dashboard for Science Inquiry. Journal of Learning Analytics 8, 2 (Sep. 2021), 105–122.
[14]
Pierre Dillenbourg. 2015. Orchestration Graphs: Modeling Scalable Education. Taylor & Francis Group.
[15]
Yannis A. Dimitriadis. 2012. Supporting Teachers in Orchestrating CSCL Classrooms. Springer New York, New York, NY, 71–82. https://doi.org/10.1007/978-1-4614-1083-6_6
[16]
Susan B. Empson and Victoria R. Jacobs. 2008. Learning to listen to children’s mathematics. In The International Handbook of Mathematics Teacher Education, Volume 2: Tools and Processes in Mathematics Teacher Education, D Tirosh and T Wood (Eds.). Sense Publishers, The Netherlands, 257–281.
[17]
Caitlin C. Farrell and Julie A. Marsh. 2016. Contributing conditions: A qualitative comparative analysis of teachers’ instructional responses to data. Teaching and Teacher Education 60 (2016), 398–412. https://doi.org/10.1016/j.tate.2016.07.010
[18]
David Hammer, Fred Goldberg, and Sharon Fargason. 2012. Responsive teaching and the beginnings of energy in a third grade classroom. Review of Science, Mathematics and ICT Education 6, 1 (2012), 51––72.
[19]
C Hmelo-Silver and H Barrows. 2015. Problem-based learning: Goals for learning and strategies for facilitating. Purdue University Press, West Lafayette, IN, 69–84.
[20]
Kenneth Holstein, Bruce M. McLaren, and Vincent Aleven. 2019. Co-Designing a Real-Time Classroom Orchestration Tool to Support Teacher–AI Complementarity. Journal of Learning Analytics 6, 2 (Jul. 2019), 27–52.
[21]
Ilana Seidel Horn and Judith Warren Little. 2010. Attending to Problems of Practice: Routines and Resources for Professional Learning in Teachers’ Workplace Interactions. American Educational Research Journal 47, 1 (2010), 181–217. https://doi.org/10.3102/0002831209345158
[22]
Nicole Hutchins and Gautam Biswas. 2022. Teacher Noticing and Response to Students’ Computational and Engineering Design Strategies. In American Educational Research Association 2022 Symposium on AI and the Future of STEM Instruction: Designing New Models to Automate Feedback to Teachers.
[23]
Nicole Hutchins, Gautam Biswas, Miklós Maróti, Ákos Lédeczi, Shuchi Grover, Rachel Wolf, Kristen Pilner Blair, Doris Chin, Luke Conlin, Satabdi Basu, 2020. C2STEM: a System for Synergistic Learning of Physics and Computational Thinking. Journal of Science Education and Technology 29, 1 (2020), 83–100.
[24]
Nicole M Hutchins, Satabdi Basu, Kevin McElhaney, Jennifer Chiu, Sarah Fick, Ningyu Zhang, and Gautam Biswas. 2021. Coherence across conceptual and computational representations of students’ scientific models. In The International Society of the Learning Sciences Annual Meeting 2021 (Bochum, Germany). International Society of the Learning Sciences (ISLS).
[25]
Nicole M Hutchins, Emara Mona Snyder, Caitlin, Shuchi Grover, and Gautam Biswas. 2021. Analyzing debugging processes during collaborative, computational modeling in science. In The International Society of the Learning Sciences Annual Meeting 2021 (Bochum, Germany). International Society of the Learning Sciences (ISLS).
[26]
Golnaz Arastoopour Irgens, Sugat Dabholkar, Connor Bain, Philip Woods, Kevin C. Hall, Hillary Swanson, Michael S. Horn, and Uri Wilensky. 2020. Modeling and Measuring High School Students’ Computational Thinking Practices in Science. Journal of Science Education and Technology 29 (2020), 137–161.
[27]
Jennifer Jacobs and Eiji Morita. 2002. Japanese and American Teachers’ Evaluations of Videotaped Mathematics Lessons. Journal for Research in Mathematics Education 33, 3 (2002), 154–175. https://doi.org/10.2307/749723
[28]
M. Pilar Jiménez-Aleixandre, Anxela Bugallo Rodríguez, and Richard A. Duschl. 2000. “Doing the lesson” or “doing science”: Argument in high school genetics. Science Education 84, 6 (2000), 757–792.
[29]
Aaron W. Johnson, Kristen B. Wendell, and Jessica Watkins. 2017. Examining Experienced Teachers’ Noticing of and Responses to Students’ Engineering. Journal of Pre-College Engineering Education Research (J-PEER) 7, 1(2017).
[30]
Heather Johnson and Michelle Forsythe. 2015. Developing Preservice Teachers’ Knowledge of Science Teaching Through Video Clubs. Journal of Science Teacher Education 26 (06 2015), 393–417. https://doi.org/10.1007/s10972-015-9429-0
[31]
Matthew Koehler and Punya Mishra. 2009. What is technological pedagogical content knowledge (TPACK)?Contemporary issues in technology and teacher education 9, 1 (2009), 60–70.
[32]
Daniel M. Levin, David Hammer, and Janet E. Coffey. 2009. Novice Teachers’ Attention to Student Thinking. Journal of Teacher Education 60, 2 (2009), 142–154. https://doi.org/10.1177/0022487108330245
[33]
Zhicheng Liu and John Stasko. 2010. Mental Models, Visual Reasoning and Interaction in Information Visualization: A Top-down Perspective. IEEE Transactions on Visualization and Computer Graphics 16, 6(2010), 999–1008. https://doi.org/10.1109/TVCG.2010.177
[34]
Camillia F. Matuk and Bat-Sheva Linn, Marcia C.and Eylon. 2015. Technology to support teachers using evidence from student work to customize technology-enhanced inquiry units. Instructional Science 43, 2 (2015), 229–257. https://doi.org/10.1007/s11251-014-9338-1
[35]
Robert J. Mislevy and Geneva D. Haertel. 2006. Implications of Evidence-Centered Design for Educational Testing. Educational Measurement: Issues and Practice 25, 4 (2006), 6–20. https://doi.org/10.1111/j.1745-3992.2006.00075.x
[36]
NRC. 2007. Taking Science to School: Learning and Teaching Science in Grades K-8. National Academies Press. https://doi.org/10.17226/11625
[37]
Amy D. Robertson, Rachel Scherr, and David Hammer. 2016. Responsive Teaching in Science and Mathematics. Routledge, Taylor & Francis Group, New York, NY, USA.
[38]
Miriam Sherin and Rosemary Russ. 2014. Teacher Noticing via Video: The Role of Interpretive Frames. Routledge, 11–28.
[39]
Valerie J. Shute. 2008. Focus on Formative Feedback. Review of Educational Research 78, 1 (2008), 153–189. https://doi.org/10.3102/0034654307313795
[40]
Elizabeth A. van Es and Miriam Gamoran Sherin. 2002. Learning to Notice: Scaffolding New Teachers’ Interpretations of Classroom Interactions. Journal of Technology and Teacher Education 10, 4 (2002), 571–596. https://www.learntechlib.org/p/9171
[41]
Anouschka van Leeuwen. 2015. Learning analytics to support teachers during synchronous CSCL: balancing between overview and overload. Journal of Learning Analytics 2, 2 (Dec. 2015), 138–162. https://doi.org/10.18608/jla.2015.22.11
[42]
Anouschka van Leeuwen, Nikol Rummel, and Tamara van Gog. 2019. What information should CSCL teacher dashboards provide to help teachers interpret CSCL situations?International Journal of Computer-Supported Collaborative Learning (2019), 1–29.
[43]
Janet Walkoe, Michelle Wilkerson, and Andrew Elby. 2017. Technology-Mediated Teacher Noticing: A Goal for Classroom Practice, Tool Design, and Professional Development. In Proceedings of the 12th International Conference on Computer Supported Collaborative Learning (CSCL) 2017 (Philadelphia, PA, USA). International Society of the Learning Sciences.
[44]
Beth Warren and Ann S Rosebery. 1995. "This Question Is Just Too, Too Easy!" Perspectives from the Classroom on Accountability in Science.Technical Report. Washington, DC.
[45]
Jessica Watkins, Mary McCormick, Kristen Bethke Wendell, Kathleen Spencer, Elissa Milto, Merredith Portsmore, and David Hammer. 2018. Data-based conjectures for supporting responsive teaching in engineering design with elementary teachers. Science Education 102, 3 (2018), 548–570. https://doi.org/10.1002/sce.21334
[46]
Korah J. Wiley, Yannis Dimitriadis, Allison Bradford, and Marica C. Linn. 2020. From Theory to Action: Developing and Evaluating Learning Analytics for Learning Design. In Proceedings of the Tenth International Conference on Learning Analytics & Knowledge (Frankfurt, Germany) (LAK ’20). Association for Computing Machinery, New York, NY, USA, 569–578. https://doi.org/10.1145/3375462.3375540
[47]
Michelle Wilkerson-Jerde, Aditi Wagh, and Uri Wilensky. 2015. Balancing Curricular and Pedagogical Needs in Computational Construction Kits: Lessons From the DeltaTick Project. Science Education 99, 3 (2015), 465–499. https://doi.org/10.1002/sce.21157
[48]
Ningyu Zhang, Gautam Biswas, and Nicole Hutchins. 2021. Measuring and Analyzing Students’ Strategic Learning Behaviors in Open-Ended Learning Environments. International Journal of Artificial Intelligence in Education (2021).

Cited By

View all
  • (2024)Towards Designing Digital Learning Tools for Students with Cortical/Cerebral Visual Impairments: Leveraging Insights from Teachers of the Visually ImpairedProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3675636(1-18)Online publication date: 27-Oct-2024
  • (2024)A Learning Analytics Dashboard for K-12 English Teachers - Bridging the Gap Between Student Process Data and Teacher NeedsAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3631700.3665228(538-548)Online publication date: 27-Jun-2024

Index Terms

  1. Using Teacher Dashboards to Customize Lesson Plans for a Problem-Based, Middle School STEM Curriculum

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    LAK2023: LAK23: 13th International Learning Analytics and Knowledge Conference
    March 2023
    692 pages
    ISBN:9781450398657
    DOI:10.1145/3576050
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 13 March 2023

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. co-design
    2. computational modeling
    3. responsive teaching
    4. teacher dashboards

    Qualifiers

    • Research-article
    • Research
    • Refereed limited

    Conference

    LAK 2023

    Acceptance Rates

    Overall Acceptance Rate 236 of 782 submissions, 30%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)79
    • Downloads (Last 6 weeks)7
    Reflects downloads up to 16 Jan 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Towards Designing Digital Learning Tools for Students with Cortical/Cerebral Visual Impairments: Leveraging Insights from Teachers of the Visually ImpairedProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3675636(1-18)Online publication date: 27-Oct-2024
    • (2024)A Learning Analytics Dashboard for K-12 English Teachers - Bridging the Gap Between Student Process Data and Teacher NeedsAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3631700.3665228(538-548)Online publication date: 27-Jun-2024

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    HTML Format

    View this article in HTML Format.

    HTML Format

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media