Predicting students' final performance from participation in on-line discussion forums

Predicting Academic Performance Based on Students’ Blog and Microblog Posts

“…Automated prediction of student performance in technology enhanced learning settings is a popular, yet complex research issue [1,2]. The popularity comes from the value of the predictive information which can be used for advising the instructor about students at-risk, who are in need of more assistance [3].…”

“…This is due to the availability of large amounts of student behavioral data, automatically logged by these systems, such as: visits and session times, accessed resources, assessment results, online activity and involvement in chats and forums, etc. [2]. Thus, student performance prediction models based on Moodle log data have been proposed in multiple previous studies [5][6][7].…”

Intelektinė daugiaagentė mokymosi sistema, naudojanti edukacinių duomenų tyrybą

“…After a thorough analysis of different studies (Romero et al 2008;Baker and Yacef 2009;Baradwaj and Pal 2011;Verma et al 2012;Srivasatava and Srivastava 2013;Milevski and Zdravev 2013;Romero et al 2013;Campagni et al 2015), the authors came to the conclusion that basic LA/ EDM techniques, applicable in this case, should be (but not limited to) the following: (1) An attempt to classify each item in a set of data into one of the predefined sets of a learner group; (2) A clustering to determine the groups of students that need special course profiling; (3) Association rules to discover interesting relations between course elements that were used by particular students; (4) A prediction to foresee the dependencies of using a learning environment's activities/tools and the final learning outcomes of a student; (5) A learning units for particular students as well as verifying these learning units with learning analytics/educational data mining methods and techniques.…”

Exploring Students’ Engagement Patterns in SPOC Forums and their Association with Course Performance

“…Like the studies of Romero, López, Luna, and Ventura (2013) and Huang, Dasgupta, Ghosh, Manning, and Sanders (2014), we utilize numbers of notional words (NW) in all posts, notional words used per post (AN), sentences (ST), asking questions (AQ) and expressing opinions (EO) to respectively represent engagement indicators of each student in forums, wherein NW and AN are word-level features, ST, AQ and EO are sentence-level features. Especially, unlike the previous research, we only extract notional words referring to terms with specific notions, ideas or other actual meanings, such as a person, a thing, an act, an emotional orientation or an evaluation object, in contrast to a relational word without semantics.…”