Using Rasch Models for Developing Fast Technology Enhanced Learning Solutions: An Example with Emojis

Autor:	Roberto Burro, Margherita Pasini, Daniela Raccanello
Rok vydání:	2019
Předmět:	Rasch scaling Rasch model Emoji business.industry Computer science Emotions Learning analytics Rasch models Cognition Psychophysical scaling computer.software_genre Data analysis Artificial intelligence Valence (psychology) business computer Natural language processing Emojis
Zdroj:	Advances in Intelligent Systems and Computing ISBN: 9783030239893 MIS4TEL
DOI:	10.1007/978-3-030-23990-9_8
Popis:	We focus on issues related to learning analytics for predicting behavior, presenting a case in which people’s answers can be predicted on the bases of a known numeric function describing a cognitive relation. We used the Rasch scaling method following an item-response latent-trait model on questions on the valence of emojis of common use. Emojis are pictorial symbols with a high degree of humanization, nowadays increasingly frequent in computer-mediated communication (CMC). However, sometimes their meaning is ambiguous. Therefore, after quantifying how much of a property such as positive and negative valence different emojis represented, we identified the function that relates the two different judgements on the same object, specifically the positive and negative valence of each emoji. Applications of this approach can be highly relevant for learning analytics, to optimize the measurement, collection, and analysis of data about learners and their contexts for fast Technology Enhanced Learning (TEL) solutions.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bee25fbff9d074c7f511f556c49fae38 https://doi.org/10.1007/978-3-030-23990-9_8 Zobrazit plný text záznamu