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1. How teachers conceptualise shared control with an AI co‐orchestration tool: A multiyear teacher‐centred design process

   https://doi.org/10.1111/bjet.13372  

   Lawrence, LuEttaMae ; Echeverria, Vanessa ; Yang, Kexin ; Aleven, Vincent ; Rummel, Nikol ( August 2023 , British Journal of Educational Technology)

   Artificial intelligence (AI) can enhance teachers' capabilities by sharing control over different parts of learning activities. This is especially true for complex learning activities, such as dynamic learning transitions where students move between individual and collaborative learning in un‐planned ways, as the need arises. Yet, few initiatives have emerged considering how shared responsibility between teachers and AI can support learning and how teachers' voices might be included to inform design decisions. The goal of our article is twofold. First, we describe a secondary analysis of our co‐design process comprising six design methods to understand how teachers conceptualise sharing control with an AI co‐orchestration tool, calledPair‐Up. We worked with 76 middle school math teachers, each taking part in one to three methods, to create a co‐orchestration tool that supports dynamic combinations of individual and collaborative learning using two AI‐based tutoring systems. We leveraged qualitative content analysis to examine teachers' views about sharing control withPair‐Up, and we describe high‐level insights about the human‐AI interaction, including control, trust, responsibility, efficiency, and accuracy. Secondly, we use our results as an example showcasing how human‐centred learning analytics can be applied to the design of human‐AI technologies and share reflections for human‐AI technology designers regarding the methods that might be fruitful to elicit teacher feedback and ideas. Our findings illustrate the design of a novel co‐orchestration tool to facilitate the transitions between individual and collaborative learning and highlight considerations and reflections for designers of similar systems.

   What is already known about this topic:

   Artificial Intelligence (AI) can help teachers facilitate complex classroom activities, such as having students move between individual and collaborative learning in unplanned ways.

   Designers should use human‐centred design approaches to give teachers a voice in deciding what AI might do in the classroom and if or how they want to share control with it.

   What this paper adds:

   Presents teacher views about how they want to share control with AI to support students moving between individual and collaborative learning.

   Describes how we adapted six design methods to design AI features.

   Illustrates a complete, iterative process to create human‐AI interactions to support teachers as they facilitate students moving from individual to collaborative learning.

   Implications for practice:

   We share five implications for designers that teachers highlighted as necessary when designing AI‐features, including control, trust, responsibility, efficiency and accuracy.

   Our work also includes a reflection on our design process and implications for future design processes.

    

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2. Facilitating Learner-Centered Interactions Through Applied Improvisation

   Skinner, R. ; Harlow, D. ; Gunther, D. ; Wesolowski, K. J. ; Marckwordt, J. ; Muller, A. ( July 2022 , Connected science learning)

   Learner-centered interactions, whether in formal or informal settings, are by their nature unscripted and require both the educator and learner to improvise. In fact, improvisation skills have been recognized as beneficial and applied in a variety of professional development training programs (including science communication, organizational development in university administration, teambuilding and leadership in business, and communication skills in medical education); yet, their inclusion in educator training has been limited. MOXI and UCSB partnered with a professional actor and theater instructor (third author of this paper) to implement applied improvisation training to support informal educators' skills development. After four years of incorporating applied improvisation training in our facilitation training program, we have found that the basic skills of listening, observing, and responding that are critical in learner-centered education are taught effectively through the well-developed, practical, and fun exercises of improvisational theater. In this article, we describe our applied improvisation training and how it builds skills pertinent to implementing learner-centered facilitation, how graduates of our training program connected applied improvisation training to their facilitation, and how other institutions can incorporate it into preparing educators for working in either informal or formal settings. 

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3. An empirical analysis of high school students' practices of modelling with unstructured data

   https://doi.org/10.1111/bjet.13253  

   Jiang, Shiyan ; Nocera, Amato ; Tatar, Cansu ; Yoder, Michael Miller ; Chao, Jie ; Wiedemann, Kenia ; Finzer, William ; Rosé, Carolyn P. ( July 2022 , British Journal of Educational Technology)

   To date, many AI initiatives (eg, AI4K12, CS for All) developed standards and frameworks as guidance for educators to create accessible and engaging Artificial Intelligence (AI) learning experiences for K‐12 students. These efforts revealed a significant need to prepare youth to gain a fundamental understanding of how intelligence is created, applied, and its potential to perpetuate bias and unfairness. This study contributes to the growing interest in K‐12 AI education by examining student learning of modelling real‐world text data. Four students from an Advanced Placement computer science classroom at a public high school participated in this study. Our qualitative analysis reveals that the students developed nuanced and in‐depth understandings of how text classification models—a type of AI application—are trained. Specifically, we found that in modelling texts, students: (1) drew on their social experiences and cultural knowledge to create predictive features, (2) engineered predictive features to address model errors, (3) described model learning patterns from training data and (4) reasoned about noisy features when comparing models. This study contributes to an initial understanding of student learning of modelling unstructured data and offers implications for scaffolding in‐depth reasoning about model decision making.

   What is already known about this topic

   Scholarly attention has turned to examining Artificial Intelligence (AI) literacy in K‐12 to help students understand the working mechanism of AI technologies and critically evaluate automated decisions made by computer models.

   While efforts have been made to engage students in understanding AI through building machine learning models with data, few of them go in‐depth into teaching and learning of feature engineering, a critical concept in modelling data.

   There is a need for research to examine students' data modelling processes, particularly in the little‐researched realm of unstructured data.

   What this paper adds

   Results show that students developed nuanced understandings of models learning patterns in data for automated decision making.

   Results demonstrate that students drew on prior experience and knowledge in creating features from unstructured data in the learning task of building text classification models.

   Students needed support in performing feature engineering practices, reasoning about noisy features and exploring features in rich social contexts that the data set is situated in.

   Implications for practice and/or policy

   It is important for schools to provide hands‐on model building experiences for students to understand and evaluate automated decisions from AI technologies.

   Students should be empowered to draw on their cultural and social backgrounds as they create models and evaluate data sources.

   To extend this work, educators should consider opportunities to integrate AI learning in other disciplinary subjects (ie, outside of computer science classes).

    

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4. 127th Annual American Society for Engineering Education Conference

   Slowinski, Mary ; Temple, Gabrielle ; Walz, Ken ( June 2020 , International Faculty Professional Development: Utilizing Hybrid Environments to Deepen Learning and Grow Community)

   null (Ed.)

   In 2018, the Center for Renewable Energy Advanced Technological Education (CREATE) received funding from the National Science Foundation to administer an Energy Storage Project with the overarching goal of advancing the renewable energy sector by facilitating integration of energy storage technology into existing two-year college programs. The goals for this project included gathering expertise, conducting job task and curriculum gap analyses, producing instructional materials, implementing pilot energy storage courses, and providing professional development for college instructors. The project's initial task was to work with educators to gather knowledge and expertise around energy storage technologies and energy education. Widespread adoption of energy storage is only beginning in the U.S. and, subsequently, energy storage-related educational programs are few; conversely, energy storage education efforts have already been pioneered and established in Europe, most notably in Germany. As a result, CREATE leveraged its history of improving energy education through international cooperation and organized a study tour to Germany for nine renewable energy educators to examine innovations in renewable energy and energy storage and to research how these technologies are incorporated into German workforce preparation. In the planning and conducting international professional development opportunities for educators, two distinct challenges arise: that of ensuring academic rigor and of anchoring and capturing learning, especially given the additional cognitive load presented by being abroad. CREATE employs an evidence-based, international collaboration model - developed and improved over the course of two previous study tours - to meet these challenges. The learning plan consists of pre-travel online activities, knowledge capture and collaborative sharing during travel, and post travel reflection. These activities combine to support educators in gathering and preserving knowledge gains and to facilitate collaborative knowledge-building that leverages the expertise and skills of the participant cohort. While this paper presents the results of the CREATE professional development model, however the findings are not limited to energy storage or to the energy sector. Indeed, this analysis and the resulting set of recommended practices should be of interest to anyone interested in creating a meaningful educator professional development opportunity, especially if international travel is incorporated. 

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5. Situating presence within extended reality for teacher training: Validation of the extended Reality Presence Scale (XRPS) in preservice teacher use of immersive 360 video

   https://doi.org/10.1111/bjet.13058  

   Gandolfi, Enrico ; Kosko, Karl W. ; Ferdig, Richard E. ( December 2020 , British Journal of Educational Technology)

   The use of video is commonplace for professional preparation in education and other fields. Research has provided evidence that the use of video in these contexts can lead to increased noticing and reflection. However, educators now have access to evolving forms of video such as 360 video. The purpose of this study was to adapt and validate an instrument for assessing immersive 360 video use in an undergraduate preservice teacher university training program. Data provided evidence of the validity of theExtended Reality Presence Scale(XRPS) for 360 video research in preservice teacher professional development. Moreover, evidence from the study suggests that those with higher feelings of presence are less likely to jump around (or twitch) while watching 360 videos. The main implications are that: a) the XRPS is a validated and reliable instrument and b) more research is needed to examine the presence and practices for in‐service and preservice teachers while watching 360 video.

   What is already known about this topic?

   Instructional videos are widely used in preservice teacher training.

   360 videos show promise for improving preservice teacher professional development in terms of immersion and presence.

   What this paper adds?

   An instrument for assessing 360 video teacher presence is presented (XRPS), targeting a current gap in the literature.

   Data provided evidence of the validity of the tool for future 360 video research and integration.

   Implications for practice and/or policy

   Practitioners can use XRPS for assessing preservice teachers’ experiences in immersive environments and evaluating 360 videos.

   Higher feelings of presence are associated with more focused viewpoints. Therefore, practitioners should support and facilitate this watching behavior.

   Higher scores of presence are associated with a perceived sense of agency and emotional attachment. Therefore, 360 videos should include design elements promoting these feelings.

    

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