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  1. This paper investigates the decision-making outcomes and cognitive-physical load implications of integrating a Building Information Modeling-driven Augmented Reality (AR) system into retrofitting design and how movement is best leveraged to understand daylighting impacts. We conducted a study with 128 non-expert participants, who were asked to choose a window facade to improve an interior space. We found no significant difference in the overall decision-making outcome between those who used an AR tool or a conventional desktop approach and that greater eye movement in AR was related to non-experts better balancing the complicated impacts facades have on daylight, aesthetics, and energy. 
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    Free, publicly-accessible full text available March 16, 2025
  2. Augmented Reality (AR) tools have shown significant potential in providing on-site visualization of Building Information Modeling (BIM) data and models for supporting construction evaluation, inspection, and guidance. Retrofitting existing buildings, however, remains a challenging task requiring more innovative solutions to successfully integrate AR and BIM. This study aims to investigate the impact of AR+BIM technology on the retrofitting training process and assess the potential for future on-site usage. We conducted a study with 64 non expert participants, who were asked to perform a common retrofitting procedure of an electrical outlet installation using either an AR+BIM system or a standard printed blueprint documentation set. Our findings indicate that AR+BIM reduced task time significantly and improved performance consistency across participants, while also decreasing the physical and cognitive demands of the training. This study provides a foundation for augmenting future retrofitting construction research that can extend the use of AR+BIM technology, thus facilitating more efficient retrofitting of existing buildings. A video presentation of this article and all supplemental materials are available at https://github.com/DesignLabUCF/SENSEable_RetrofittingTraining. 
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    Free, publicly-accessible full text available November 1, 2024
  3. Introduction

    Self-regulated learning (SRL), or learners’ ability to monitor and change their own cognitive, affective, metacognitive, and motivational processes, encompasses several operations that should be deployed during learning including Searching, Monitoring, Assembling, Rehearsing, and Translating (SMART). Scaffolds are needed within GBLEs to both increase learning outcomes and promote the accurate and efficient use of SRL SMART operations. This study aims to examine how restricted agency (i.e., control over one’s actions) can be used to scaffold learners’ SMART operations as they learn about microbiology with Crystal Island, a game-based learning environment.

    Methods

    Undergraduate students (N = 94) were randomly assigned to one of two conditions: (1) Full Agency, where participants were able to make their own decisions about which actions they could take; and (2) Partial Agency, where participants were required to follow a pre-defined path that dictated the order in which buildings were visited, restricting one’s control. As participants played Crystal Island, participants’ multimodal data (i.e., log files, eye tracking) were collected to identify instances where participants deployed SMART operations.

    Results

    Results from this study support restricted agency as a successful scaffold of both learning outcomes and SRL SMART operations, where learners who were scaffolded demonstrated more efficient and accurate use of SMART operations.

    Discussion

    This study provides implications for future scaffolds to better support SRL SMART operations during learning and discussions for future directions for future studies scaffolding SRL during game-based learning.

     
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    Free, publicly-accessible full text available November 9, 2024
  4. Abstract

    Intelligent tutoring systems (ITSs) incorporate pedagogical agents (PAs) to scaffold learners' self‐regulated learning (SRL) via prompts and feedback to promote learners' monitoring and regulation of their cognitive, affective, metacognitive and motivational processes to achieve their (sub)goals. This study examines PAs' effectiveness in scaffolding and teaching SRL during learning with MetaTutor, an ITS on the human circulatory system. Undergraduates (N = 118) were randomly assigned to a condition:Control Condition(i.e. learners could only self‐initiate SRL strategies) andPrompt and Feedback Condition(i.e. PAs prompted learners to engage in SRL). Learners' log‐file data captured when strategies were used, the initiator of the strategy (i.e. learner and PA), and the relevance of instructional content pages in relation to learner subgoals. While results showed that PAs were effective scaffolders of SRL in which they prompted learners to engage in SRL strategies more when content was relevant towards their subgoals and as time on page and task increased, there were mixed findings about the effectiveness of PAs as teachers of SRL. Findings show how production rules guiding PA prompts can improve their scaffolding and teaching of SRL across the learning task – through contextualizing SRL strategies to the instructional content and in relation to the relevance of the content to learners' subgoals.Practitioner notesWhat is already known about this topic

    Most learners struggle to efficiently and effectively use self‐regulated learning (SRL) strategies to attain goals and subgoals.

    There is a need for SRL to be scaffolded for learners to manage multiple goals and subgoals while learning about complex STEM topics.

    Intelligent tutoring systems (ITSs) typically incorporate pedagogical agents (PAs) to prompt learners to engage in SRL strategy and provide feedback.

    There are mixed findings on the effectiveness of PAs in scaffolding learners' SRL.

    What this paper adds

    We consider PAs not only scaffolders but also teachers of SRL.

    Results showed that while PAs encouraged the use of SRL strategies when the content was relevant to subgoals, they did not discourage the use of SRL strategies when the content was not relevant.

    Results for this study were mixed in their support of PAs as teachers of SRL.

    Learners increasingly depended on PAs to prompt SRL strategies as time on task progressed.

    Implications for practice and/or policy

    PAs are effective scaffolders of SRL with more research needed to understand their role as teachers of SRL.

    PA scaffolding is more essential as time on task progresses.

    When deploying specific cognitive and metacognitive SRL strategies, the relevance of the content to learners' subgoals should be taken into account.

     
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  5. Building facades are components that shape a structure’s daylighting, energy use, and view factors. This paper presents an approach that enables designers to understand the impact that different facade designs will have over time and space in the built environment through a BIM-enabled augmented reality system. The system permits the examination of a range of facade retrofit scenarios and visualizes the daylighting simulations and aesthetics of a structure while retaining function and comfort. A focus of our study was to measure how participants make decisions within the multiobjective decision space designers often face when buildings undergo retrofitting. This process often requires designers to search for a set of alternatives that represent the optimal solution. We analyze the decision-making process of forty-four subjects to determine how they explore design choices. Our results indicate the feasibility of using BIM-enabled AR to improve how designers make informed decisions. 
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  6. Undergraduate students ( N = 82) learned about microbiology with Crystal Island, a game-based learning environment (GBLE), which required participants to interact with instructional materials (i.e., books and research articles, non-player character [NPC] dialogue, posters) spread throughout the game. Participants were randomly assigned to one of two conditions: full agency , where they had complete control over their actions, and partial agency , where they were required to complete an ordered play-through of Crystal Island. As participants learned with Crystal Island, log-file and eye-tracking time series data were collected to pinpoint instances when participants interacted with instructional materials. Hierarchical linear growth models indicated relationships between eye gaze dwell time and (1) the type of representation a learner gathered information from (i.e., large sections of text, poster, or dialogue); (2) the ability of the learner to distinguish relevant from irrelevant information; (3) learning gains; and (4) agency. Auto-recurrence quantification analysis (aRQA) revealed the degree to which repetitive sequences of interactions with instructional material were random or predictable. Through hierarchical modeling, analyses suggested that greater dwell times and learning gains were associated with more predictable sequences of interaction with instructional materials. Results from hierarchical clustering found that participants with restricted agency and more recurrent action sequences had greater learning gains. Implications are provided for how learning unfolds over learners' time in game using a non-linear dynamical systems analysis and the extent to which it can be supported within GBLEs to design advanced learning technologies to scaffold self-regulation during game play. 
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