OPPIA: A Context-Aware Ubiquitous Learning Platform to Exploit Short-Lived Student Networks for Collaborative Learning

Abstract

We present the OPPIA platform, a ubiquitous and smart learning environment, that deploys sporadic learning networks (SLNs) among people (students, teachers and experts) who happen to be in a common place or in a remote place but connected to the platform through the Internet. The idea is to establish dynamic learning networks that encourage their members to work together and create a learning environment with proper resources and activities to satisfy their learning needs. This paper describes the design of the platform from the lowest levels of establishing connections among members of the SLNs, up to the highest level of smart learning services.

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

“…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], [39], [50], [55], [62], [69]- [72], [79], [80], [86] Cameras 11 (13.41%) [20], [34], [35], [43], [44], [47], [49], [52], [63], [65], [66] Microcontrollers 7 (10.29%) [34], [47], [48], [58], [59], [66], [67] Virtual/remote laboratories 6 (8.82%) [20], [47], [53], [73], [74], [82] Biometric sensors 5 (7.35%) [34], [52], [66], [67], [71] Environmental sensors 5 (7.35%) [41], [53], [59], [66],…”

“…[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],…”