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1. Why experience matters to privacy: How context-based experience moderates consumer privacy expectations for mobile applications

   https://doi.org/10.1002/asi.23500  

   Martin, Kirsten ; Shilton, Katie ( August 2016 , Journal of the Association for Information Science and Technology)
2. Inferring #MeToo Experience Tweets using Classic and Neural Models [Inferring #MeToo Experience Tweets using Classic and Neural Models]

   https://doi.org/10.5220/0011278100003269  

   Zech, Julianne ; Singh, Lisa ; Kawintiranon, Kornraphop ; Mezey, Naomi ; Williams, Jamillah ( January 2022 , Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA)

   The #MeToo movement is one of several calls for social change to gain traction on Twitter in the past decade. The movement went viral after prominent individuals shared their experiences, and much of its power continues to be derived from experience sharing. Because millions of #MeToo tweets are published every year, it is important to accurately identify experience-related tweets. Therefore, we propose a new learning task and compare the effectiveness of classic machine learning models, ensemble models, and a neural network model that incorporates a pre-trained language model to reduce the impact of feature sparsity. We find that even with limited training data, the neural network model outperforms the classic and ensemble classifiers. Finally, we analyze the experience-related conversation in English during the first year of the #MeToo movement and determine that experience tweets represent a sizable minority of the conversation and are moderately correlated to major events. 

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3. Instructional Design, Situational Interest, and User Experience: Applications of Learning Experience Design to Promote Children’s Online Engagement. In de Vries, E., Hod, Y., & Ahn, J. (Eds.), Proceedings of the 15th International Conference of the Learning Sciences - ICLS 2021. (pp. 521-524). Bochum, Germany: International Society of the Learning Sciences.

   Wong, J. ( June 2021 , Proceedings of the 15th International Conference of the Learning Sciences - ICLS 2021.)

   de Vries, E. (Ed.)

   Historically, learning for young students has occurred in formal, in-person classroom environments. But in just a matter of weeks, children were mandated to transition to a completely new mode of learning, facing new learning challenges with heightened anxieties. To this end, we aim to better understand how our learning experience design (LXD) efforts support or hinder children’s engagement while participating in an online, video-based math course. This study operationalized LXD through the integration of e-learning instructional design (ID) as a lever for promoting students’ situational interest (SI), emphasis on human-centered design to support students’ user experience (UX), and the combination of SI and UX to foster student engagement in an online environment. Results provide practical implications for how we can intentionally iterate our designs to sustain children’s online engagement as we prepare for future instances of traditional, online and even hybrid models of instruction. 

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4. Explaining the description-experience gap in risky decision-making: learning and memory retention during experience as causal mechanisms

   https://doi.org/10.3758/s13415-023-01099-z  

   Haines, Nathaniel ; Kvam, Peter D. ; Turner, Brandon M. ( June 2023 , Cognitive, Affective, & Behavioral Neuroscience)

   When making decisions based on probabilistic outcomes, people guide their behavior using knowledge gathered through both indirect descriptions and direct experience. Paradoxically, how people obtain information significantly impacts apparent preferences. A ubiquitous example is the description-experience gap: individuals seemingly overweight low probability events when probabilities are described yet underweight them when probabilities must be experienced firsthand. A leading explanation for this fundamental gap in decision-making is that probabilities are weighted differently when learned through description relative to experience, yet a formal theoretical account of the mechanism responsible for such weighting differences remains elusive. We demonstrate how various learning and memory retention models incorporating neuroscientifically motivated learning mechanisms can explain why probability weighting and valuation parameters often are found to vary across description and experience. In a simulation study, we show how learning through experience can lead to systematically biased estimates of probability weighting when using a traditional cumulative prospect theory model. We then use hierarchical Bayesian modeling and Bayesian model comparison to show how various learning and memory retention models capture participants’ behavior over and above changes in outcome valuation and probability weighting, accounting for description and experience-based decisions in a within-subject experiment. We conclude with a discussion of how substantive models of psychological processes can lead to insights that heuristic statistical models fail to capture. 

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5. Experience‐Driven Semantic Differentiation: Effects of a Naturalistic Experience on Within‐and Across‐Domain Differentiation in Children

   https://doi.org/doi.org/10.1111/cdev.13369  

   Vales, C ; States, S.L ; Fisher, A.V. ( April 2020 , Child development)

   Organized semantic networks reflecting distinctions within and across domains of knowledge are critical for higher‐level cognition. Thus, understanding how semantic structure changes with experience is a fundamental question in developmental science. This study probed changes in semantic structure in 4–6 year‐old children (N = 29) as a result of participating in an enrichment program at a local botanical garden. This study presents the first direct evidence that (a) the accumulation of experience with items in a domain promoted increases in both within‐ and across‐domain semantic differentiation, and that (b) this experience‐driven semantic differentiation generalized to nonexperienced items. These findings have implications for understanding the role of experience in building semantic networks, and for conceptualizing the contribution of enrichment experiences to academic success. 

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