An Approach to Measure Coding Competency Evolution

Affordances and Core Functions of Smart Learning Environments: A Systematic Literature Review

“…According to this classification, Kinshuk (n = 8), Kumar (n = 3), Boulanger (n = 3) and Seanosky (n = 3) are the most relevant authors. Kinshuk, Boulanger, and Seanosky have co-authored 3 publications [21]- [23], whereas Kumar has also co-authored 2 publications with them [21], [22]. Exploring the number of citations in Google Scholar (see right vertical axis in Fig.…”

“…Likewise, SLEs might collect multiple samples along the learning activity to trace stakeholders' actions and reactions. Technology plays a key [19]- [22], [25]- [32], [38], [40], [41], [45]- [47], [49], [51], [53], [54], [56]- [60], [62]- [76] Traceable (tracking and monitoring features) 21 (30.88%) role in SLEs collecting contextual information, which could refer to [85]: (i) identification of the stakeholder (e.g., through face recognition, person identification) or an object (e.g., RFID); (ii) timestamp when learning activities are performed, to record the time where the learning activity is performed;…”

“…Learning management systems (LMSs) were referenced in [28], [29], [35], [38], [39], [42]- [46], [49], [50], [53], [58], [59], [62], [63], [87], [88] Desktop computers 17 (25%) [19], [21], [22], [24], [31], [33], [40], [42], [43], [60], [63], [64], [67], [73], [77], [78], [87] Learning management system 14 (20.59%)…”

“…[21]- [23], [30], [31], [36], [38], [41], [50], [53], [57], [61], [68], [70], [71], [79], [80] Data mining 9 (13.24%) [22], [27], [31], [36], [54], [67], [69], [72], [80] Ontologies 6 (8.82%) [21], [22], [25], [32], [60], [62] Artificial intelligence 6 (8.82%) [19], [54], [59], [66], [75], [78] Cloud computing 5 (7.35%) [34], [44], [55], [56] favored the inclusion of data processing and analysis techniques in SLEs (see Table V). The results of the analysis are presented considering that some of these data processing techniques might overlap in specific taxonomies.…”

“…Ontologies are frequently used in educational contexts to formulate models of knowledge that can be understood by both humans and machines. For example, the work by Lalingkar [28], [29], [35], [38], [39], [42]- [46], [49], [50], [53], [58], [59], [62], [63], [87], [88] Desktop computers 17 (25%) [19], [21], [22], [24], [31], [33], [40], [42], [43], [60], [63], [64], [67], [73], [77], [78], [87] Data visualizations 12 (17.65%) [21], [28], [41], [50], [53], [55], [58], [70], [71], [73], [80], [84] Videos 7 (10.29%) [30], [34], [43], [46],…”