Abstract: Educational innovation is a field that has been greatly enriched by using technology in its processes, resulting in a learning model where information comes from numerous sources and collaboration takes place among multiple students. One attractive challenge within educational innovation is the design of collaborative learning activities from the social computing point of view, where collaboration is not limited to student-to-student relationships, but includes student-to-machine interactions. At the same time, there is a great lack of tools that give support to the whole learning process and are not restricted to specific aspects of the educational task. In this paper, we present and evaluate context-aware framework for collaborative learning applications (CAFCLA) as a solution to these problems. CAFCLA is a flexible framework that covers the entire process of developing collaborative learning activities, taking advantage of contextual information and social interactions. Its application in the experimental case study of a collaborative WebQuest within a museum has shown that, among other benefits, the use of social computing improves the learning process, fosters collaboration, enhances relationships, and increases engagement.

社会计算下的协作学习

[1]Al Maghayreh E, Samarah S, Alkhateeb F, et al., 2012. A framework for monitoring the execution of distributed multi-agent programs. Int J Adv Sci Technol, 38(1):53-66.

[2]Arif M, Illahi M, Karim A, et al., 2015. An architecture of agent-based multi-layer interactive e-learning and e-testing platform. Qual Quant, 49(6):2435-2458.

[3]Barzilai S, Blau I, 2014. Scaffolding game-based learning: impact on learning achievements, perceived learning, and game experiences. Comput Educ, 70:65-79.

[4]Bellifemine F, Poggi A, Rimassa G, 2001. JADE: a FIPA2000 compliant agent development environment. Proc 5^th Int Conf on Autonomous Agents, p.216-217.

[5]Bellifemine FL, Caire G, Greenwood D, 2007. Developing Multi-agent Systems with JADE. John Wiley & Sons Ltd., Hoboken, USA.

[6]Berjón R, Beato ME, Mateos M, et al., 2015. SCHOM. A tool for communication and collaborative e-learning. Comput Human Behav, 51:1163-1171.

[7]Castro GG, Domínguez EL, Velázquez YH, et al., 2016. MobiLearn: context-aware mobile learning system. IEEE Latin Am Trans, 14(2):958-964.

[8]Chen CH, Chou MH, 2015. Enhancing middle school students’ scientific learning and motivation through agent-based learning. J Comput Assist Learn, 31(5):481-492.

[9]Chou TL, Chanlin LJ, 2014. Location-based learning through augmented reality. J Educ Comput Res, 51(3):355-368.

[10]Chuang HH, 2016. Leveraging CRT awareness in creating web-based projects through use of online collaborative learning for pre-service teachers. Educ Technol Res Dev, 64(4):857-876.

[11]Cox MJ, 2013. Formal to informal learning with IT: research challenges and issues for e-learning. J Comput Assist Learn, 29(1):85-105.

[12]Crawford L, Higgins KN, Huscroft-D’Angelo JN, et al., 2016. Students’ use of electronic support tools in mathematics. Educ Technol Res Dev, 64(6):1163-1182.

[13]Cress U, Kimmerle J, 2008. A systemic and cognitive view on collaborative knowledge building with wikis. Int J Comput-Support Collab Learn, 3(2):105-122.

[14]Dascalu MI, Bodea CN, Moldoveanu A, et al., 2015. A recommender agent based on learning styles for better virtual collaborative learning experiences. Comput Human Behav, 45:243-253.

[15]de Marziani C, Ureña J, Hernandez Á, et al., 2009. Acoustic sensor network for relative positioning of nodes. Sensors, 9(11):8490-8507.

[16]Dey AK, 2001. Understanding and using context. Pers Ubiq Comput, 5(1):4-7.

[17]Enembreck F, Barthès JPA, 2013. A social approach for learning agents. Expert Syst Appl, 40(5):1902-1916.

[18]Erickson T, Kellogg WA, 2000. Social translucence: an approach to designing systems that support social processes. ACM Trans Comput-Human Int, 7(1):59-83.

[19]Fermoso AM, Mateos M, Beato ME, et al., 2015. Open linked data and mobile devices as e-tourism tools. A practical approach to collaborative e-learning. Comput Human Behav, 51:618-626.

[20]García Ó, Tapia DI, Alonso RS, et al., 2012. Ambient intelligence and collaborative e-learning: a new definition model. J Amb Intell Hum Comput, 3(3):239-247.

[21]García-Floriano A, Ferreira-Santiago A, Yáñez-Márquez C, et al., 2017. Social web content enhancement in a distance learning environment: intelligent metadata generation for resources. Int Rev Res Open Dist Learn, 18(1):161-176.

[22]Garrido A, Morales L, Serina I, 2016. On the use of case-based planning for e-learning personalization. Expert Syst Appl, 60:1-15.

[23]Hwang GJ, Wu PH, 2014. Applications, impacts and trends of mobile technology-enhanced learning: a review of 2008- 2012 publications in selected SSCI journals. Int J Mob Learn Organ, 8(2):83-95.

[24]Jin X, Gallagher A, Cao LL, et al., 2010. The wisdom of social multimedia: using flickr for prediction and forecast. Proc 18^th ACM Int Conf on Multimedia, p.1235-1244.

[25]Jung JJ, 2009. Social grid platform for collaborative online learning on blogosphere: a case study of eLearning@ BlogGrid. Expert Syst Appl, 36(2):2177-2186.

[26]Kirschner PA, Kreijns K, Phielix C, et al., 2015. Awareness of cognitive and social behaviour in a CSCL environment. J Comput Assist Learn, 31(1):59-77.

[27]Laine TH, Joy M, 2009. Survey on context-aware pervasive learning environments. Int J Int Mob Technol, 3(1):70-76.

[28]Land SM, Zimmerman HT, 2015. Socio-technical dimensions of an outdoor mobile learning environment: a three-phase design-based research investigation. Educ Technol Res Dev, 63(2):229-255.

[29]Lin JW, Mai LJ, Lai YC, 2015. Peer interaction and social network analysis of online communities with the support of awareness of different contexts. Int J Comput-Support Collab Learn, 10(2):139-159.

[30]Linden G, Smith B, York J, 2003. Amazon.com recommendations: item-to-item collaborative filtering. IEEE Int Comput, 7(1):76-80.

[31]López-Yáñez I, Yáñez-Márquez C, Camacho-Nieto O, et al., 2015. Collaborative learning in postgraduate level courses. Comput Human Behav, 51:938-944.

[32]Luna V, Quintero R, Torres M, et al., 2015. An ontology-based approach for representing the interaction process between user profile and its context for collaborative learning environments. Comput Human Behav, 51:1387-1394.

[33]Marin-Perianu M, Meratnia N, Havinga P, et al., 2007. Decentralized enterprise systems: a multiplatform wireless sensor network approach. IEEE Wirel Commun, 14(6):57- 66.

[34]Masud M, 2016. Collaborative e-learning systems using semantic data interoperability. Comput Human Behav, 61: 127-135.

[35]Melero J, Hernández-Leo D, Manatunga K, 2015. Group- based mobile learning: do group size and sharing mobile devices matter? Comput Human Behav, 44:377-385.

[36]Mora HM, Pont MTS, de Miguel Casado G, et al., 2015. Management of social networks in the educational process. Comput Human Behav, 51:890-895.

[37]Musser D, Wedman J, Laffey J, 2003. Social computing and collaborative learning environments. Proc 3^rd IEEE Int Conf on Advanced Technologies, p.520-521.

[38]Nebusens, 2018. n-Core®: a faster and easier way to create wireless sensor networks. http://www.n-core.info

[39]Novak E, 2015. A critical review of digital storyline-enhanced learning. Educ Technol Res Dev, 63(3):431-453.

[40]Parameswaran M, Whinston AB, 2007. Research issues in social computing. J Assoc Inform Syst, 8(6):336-350.

[41]Prieto J, Mazuelas S, Bahillo A, et al., 2012. Adaptive data fusion for wireless localization in harsh environments. IEEE Trans Signal Process, 60(4):1585-1596.

[42]Prieto J, de Paz JF, Villarrubia G, et al., 2015. Unified fingerprinting/ranging localization in harsh environments. Int J Distr Sens Networks, 11(11):1-11.

[43]Prieto J, Mazuelas S, Win MZ, 2016. Context-aided inertial navigation via belief condensation. IEEE Trans Signal Process, 64(12):3250-3261.

[44]Robertson D, Giunchiglia F, 2013. Programming the social computer. Phil Trans A, 371(1987):20120379.

[45]Rodríguez S, Julián V, Bajo J, et al., 2011. Agent-based virtual organization architecture. Eng Appl Artif Intell, 24(5): 895-910.

[46]Roschelle J, 2003. Keynote paper: unlocking the learning value of wireless mobile devices. J Comput Assist Learn, 19(3):260-272.

[47]Ryokai K, Farzin F, Kaltman E, et al., 2013. Assessing multiple object tracking in young children using a game. Educ Technol Res Dev, 61(2):153-170.

[48]Schroeder A, Minocha S, Schneider C, 2010. The strengths, weaknesses, opportunities and threats of using social software in higher and further education teaching and learning. J Comput Assist Learn, 26(3):159-174.

[49]Schuler D, 1994. Social computing. Commun ACM, 37(1):28- 29.

[50]Shadbolt N, 2013. Knowledge acquisition and the rise of social machines. Int J Hum-Comput Stud, 71(2):200-205.

[51]Sinha S, Rogat TK, Adams-Wiggins KR, et al., 2015. Collaborative group engagement in a computer-supported inquiry learning environment. Int J Comput-Support Collab Learn, 10(3):273-307.

[52]Sun G, Shen J, 2014. Facilitating social collaboration in mobile cloud-based learning: a teamwork as a service (TaaS) approach. IEEE Trans Learn Technol, 7(3):207-220.

[53]Villarrubia G, de Paz JF, Bajo J, et al., 2014. Ambient agents: embedded agents for remote control and monitoring using the PANGEA platform. Sensors, 14(8):13955-13979.

[54]von Ahn L, Blum M, Langford J, 2004. Telling humans and computers apart automatically. Commun ACM, 47(2):56- 60.

[55]Wang FY, Carley KM, Zeng D, et al., 2007. Social computing: from social informatics to social intelligence. IEEE Intell Syst, 22(2):79-83.

[56]Zampella F, Bahillo A, Prieto J, et al., 2013. Pedestrian navigation fusing inertial and RSS/TOF measurements with adaptive movement/measurement models: experimental evaluation and theoretical limits. Sens Actuat A, 203:249- 260.

[57]Zhang YQ, Zhang PL, 2015. Machine training and parameter settings with social emotional optimization algorithm for support vector machine. Patt Recogn Lett, 54:36-42.

[58]Zhao K, Chan CKK, 2014. Fostering collective and individual learning through knowledge building. Int J Comput- Support Collab Learn, 9(1):63-95.