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1. A Formative Evaluation on a Virtual Reality Game-Based Learning System for Teaching Introductory Archaeology

   Shackelford, Laura; Huang, Wenhao David; Craig, Alan; Merrill, Cameron; Chen, Danyin; Arjona, Jamie (October 2018, E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education)

   null (Ed.)

   Virtual reality (VR) holds great potential for instructional and educational purposes as it is capable of immersing learners cognitively, physiologically, and emotionally by transcending physical limitations and boundaries, so learners can acquire experiences otherwise unattainable. A case in point is a VR learning environment that allows archaeology instructors to teach a variety of concepts and skills on archaeological fieldwork without bringing students to actual archaeological sites. A VR environment would also enable students to practice newly acquired skills in a safer and more affordable space than physically visiting the sites. VR alone, however, is insufficient to engage learners. Therefore, we identify game-based learning strategies to guide the development of the VR archaeology environment by incorporating game structure, game involvement, and game appeal into the design. The presentation reports an NSF-funded project that utilizes the HTC Vive VR system to host a game-based learning environment for teaching introductory archaeology classes in a US Midwestern university. The manuscript reports the design, development, and formative evaluation of the VR archaeology game grounded in learners’ motivational and cognitive processes. In particular, the formative evaluation findings, based on 40 participants' responses, reveal various design opportunities and challenges for designing game-based learning experience in virtual reality environments. 

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2. Motivators Matter When Gamifying Learning Activities

   https://doi.org/10.1007/978-3-031-26876-2_89  

   Dichev, C.; Dicheva, D.; Ismailova, R. (March 2023, 25th International Conference on Interactive Collaborative Learning (ICL2022))

   Auer, M.E.; Pachatz, W.; Rüütmann, T. (Ed.)

   Gamification, the use of game design elements in non-game contexts, has become a promising strategy for enhancing learners’ motivation, engagement, and performance. However, our understanding of how the motivational affordances of gamification interact with the motivational drivers engendered by a learning activity is still limited. In most of the studies the focus is on the role of the incorporated gamification elements, disregarding motivational factors associated with the learning activity, such as perceived utility, expectancy of success, and needed effort to complete it. Expectancy-Value model offers a practical method for estimating the level and quality of learners’ motivation towards a particular task as it accounts for both intrinsic and extrinsic motivators. Employing this model can shed a new light on the motivational potential of educational gamification. Accordingly, in this paper we present experiments with Expectancy-Value-Cost scale (EVC) as an instrument for estimating the level of students’ motivation towards a gamified learning activity. We studied empirically how the motivational factors measured by EVC relate to the level of learners’ engagement in gamified practicing and assessed their predictive qualities. 

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3. Stirring a Secret Sauce: A Literature Review on the Conditions and Effects of Authentic Learning

   https://doi.org/10.1007/s10648-022-09676-3  

   Nachtigall, V.; Shaffer, D. W.; Rummel, N. (January 2022, Educational psychology review)

   The present conceptual literature review analyzes 50 studies that systematically examined the effects of authentic learning settings on cognitive or motivational learning outcomes. The analysis focuses on describing the context of the studies, the design elements of authentic learning settings, and the pursued intentions of authenticity. The review further describes the effects of authentically designed learning settings on cognitive outcomes, motivational outcomes, and learners’ perceived authenticity revealed by previous research. Building on these findings, we conducted Epistemic Network Analysis (ENA) of contrasting cases to identify design elements and intentions of authenticity characterizing studies that show high effectiveness for cognitive and motivational outcomes versus those with low effectiveness. The ENA results suggest, for instance, that providing authentic materials (as a design element of authentic learning settings) to resemble real-life experiences (as an intention of authenticity) could be a double-edged sword, as they feature both authentically designed learning settings with low effects on cognitive outcomes and settings with high effects on motivational outcomes. Overall, the results of the present literature review point to critical limitations of previous research, such as a lack of clear definitions and operationalizations of authentic learning. Consequently, we draw specific conclusions about how future research could improve our understanding of how to create and implement powerful methods of authentic learning. 

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4. Automatic assessment of cognitive and emotional states in virtual reality‐based flexibility training for four adolescents with autism

   https://doi.org/10.1111/bjet.13005  

   Moon, Jewoong; Ke, Fengfeng; Sokolikj, Zlatko (July 2020, British Journal of Educational Technology)

   Abstract Tracking students’ learning states to provide tailored learner support is a critical element of an adaptive learning system. This study explores how an automatic assessment is capable of tracking learners’ cognitive and emotional states during virtual reality (VR)‐based representational‐flexibility training. This VR‐based training program aims to promote the flexibility of adolescents with autism spectrum disorder (ASD) in interpreting, selecting and creating multimodal representations during STEM‐related design problem solving. For the automatic assessment, we used both natural language processing (NLP) and machine‐learning techniques to develop a multi‐label classification model. We then trained the model with the data from a total of audio‐ and video‐recorded 66 training sessions of four adolescents with ASD. To validate the model, we implemented both k‐fold cross‐validations and the manual evaluations by expert reviewers. The study finding suggests the feasibility of implementing the NLP and machine‐learning driven automatic assessment to track and assess the cognitive and emotional states of individuals with ASD during VR‐based flexibility training. The study finding also denotes the importance and viability of providing adaptive supports to maintain learners’ cognitive and affective engagement in a highly interactive digital learning environment. 

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5. Gamifying learning for learners

   https://doi.org/10.1186/s41239-020-00231-0  

   Dichev, Christo; Dicheva, Darina; Irwin, Keith (December 2020, International Journal of Educational Technology in Higher Education)

   null (Ed.)

   Abstract The majority of user models in gamification are based on user’s gamer personality. However, the motivations driving individuals’ learning behavior differ from their motivations when playing. There is no evidence that learners’ experiences in gamified activities are described by these models. Thus, an alternative model capturing learners’ motivational experiences and relating them to the motivational mechanisms of gamification design is needed. To fill this gap we propose a context-specific typology which groups learners based on their type of motivation and perceived ability associated with a learning activity. The purpose of this proposal is to provide a framework for connecting each learner’s type to a set of motivational affordances to which that type is susceptible. Facilitating the task of selecting motivational affordances matching learner’s type aids the design of customized gamified learning. 

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