@article{
 title = {Applying learning analytics to students’ interaction in business simulation games. The usefulness of learning analytics to know what students really learn},
 type = {article},
 year = {2019},
 identifiers = {[object Object]},
 keywords = {Business simulation games,Data mining,Learning analytics,Learning outcomes,Online learning activities,Student interaction,business simulation games,data mining,learning analytics,learning outcomes,online learning activities},
 pages = {600-612},
 volume = {92},
 month = {3},
 publisher = {Elsevier Ltd},
 day = {1},
 id = {7e039572-a34e-3494-9cf9-bb06868542d1},
 created = {2020-02-03T14:32:51.774Z},
 accessed = {2020-02-02},
 file_attached = {false},
 profile_id = {66be748e-b1e3-36e1-95e1-5830d0ccc3ca},
 group_id = {ed1fa25d-c56b-3067-962d-9d08ff49394c},
 last_modified = {2020-02-03T14:33:03.074Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 folder_uuids = {af1b8628-85f8-4733-9f52-121159400517},
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 abstract = {Nowadays, different ways of communication and interaction among multiple actors are dominating learning processes. However, there are critical opinions that question the contribution of student interaction to real learning. This study applies learning analytics and data mining techniques to explore the online discussion forums of 362 business students at the bachelor and master levels, who participated in business simulation games between 2011 and 2016. The findings revealed that the most frequent contents in the students’ online discussion forums were related, firstly, to the parameters and features of the business simulation game, and, secondly, to elements that fostered the students’ learning process, while small talk or regular conversation did not appear to be relevant. In addition, the contents with predictive power over learning results were related to uncertainty, time, interaction, communication and collaboration, although none of these elements influenced teacher assessment of student learning. This study reveals the usefulness of learning analytics tools to gain a more wide and holistic view of the learning process of students, discovering new aspects that affect students’ learning results.},
 bibtype = {article},
 author = {Beatriz Hernández-Lara, Ana and Perera-Lluna, Alexandre and Serradell-López, Enric and Hernández-Lara, Ana Beatriz and Perera-Lluna, Alexandre and Serradell-López, Enric},
 journal = {Computers in Human Behavior}
}

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