Romero, M. Llorens, F., Perez, A., Franco, M., Hettiarachchi, E., Esposito, A. (2011). Time factor in e-learning collaborative concept map. Time factor Update Meeting, 1st June, Elearn Center. UOC.

1. Dra. Margarida Romero [email_address] Time factor Thematic Research Seminar The time factor perspectives collaborative conceptual map Presenting Ph.D. Students: Llorens, F. Perez-Poch, A. Franco-Casamitjana, M. Hettiarachchi, E. (virtual) Esposito, A. Thematic Research Seminar : Dra. Barberà, Dra. Romero Ph.D. Students: Anglada, O., Espositio, A., Llorens, F., Sabulsky, G., Vazquez, A., Castro, P., Franco-Casamitjana, M., Izquierdo, J.V., Hettiarachchi, E., Perez-Poch, A. Quesada, A.V., Medina, J.L. 1st June 2011. Elearn Center. Time factor Thematic Research Seminar Time factor Thematic Research Seminar Romero, M. Llorens, F., Perez, A., Franco, M., Hettiarachchi, E., Esposito, A.

2. Part of the PhD. Candidates participating in the Time Factor Thematic Research Seminar follow the event on Twitter #timefactor #elearning #uoc #phd

18. Knowledge Desire Skills Habits Consistent, often unconscious pattern of behaviour Control of own time often leads to Life Satisfaction: Macan, Shahani, Dipboye, Peek (1990). Behavioural time Habits

19. Personal Rythms, Adaptive Time, Acceleration Gros, Barbara & Kirschner (2010). Time personalisation Time as perception Lifelong Learner’s expectations Thorpe (2006) Integration of the studies in the lifestyle Tresman (2002) Self-paced learners and social software Anderson et al (2010) Time use expectations of NetGen students in higher eduation Ramanau et al (2010) Behavioural time

25. Time affordances of Computer Learning Environments Most studies in learning and teaching process in e-learning mainly focus on pedagogical benefits of technology and how they absorb more or less students' time (Gros, Barberà & Kirschner, 2010). Accounts on time affordances of ICTs tools and environments for learning purposes can be directly or indirectly inferred from studies in: - systematic views of distance education (Bates, 2005); - CSCL (e.g. Scardamalia and Bereiter, 1997; Dewiyanti et al., 2007 ; Sarmiento and Stahl, 2008) ; - learner experiences with ICTs as reported from educational technology research (Thorpe, 2006; Anderson et al., 2010); - approaches in design of computer-mediated environments (e.g. Jones & Warren, 2006). Otherwise, issues of time affordances can be contextualized within the wide debate on the term “affordances”.

26. Time affordances of Computer Learning Environments Bates (2005) describes inherent delivery features of technologies, that identify the main distinction of synchronous and asynchronous e-learning contexts (see also Hrastinski, 2008). Many authors studied time management and perception as 'effects' of use of asynchronous web forums (Scardamalia & Bereiter, 1994; Dewayanti e al., 2007). Other scholars (Anderson, Poellhuber & McKerlich, 2010) highlighted than in less than a decade, a plenty of new communication technologies has been disrupting the traditional model of self-paced e-learner, enabling different time patterns to be adopted within and beyond the institutional virtual learning environments. However, empirical studies (Thorpe, 2006) report that ‘email’ keeps on being perceived by e-learners as the most ‘time saving’ among ICTs.

27. Time affordances of Computer Learning Environments ‘ Efficiency’ seems to be the main time affordance of technology as expected by learners. But this can be sometimes misleading even for designers. In fact, more complex digital environments are emerging and challenging the popular assumption of technology as a learning accelerator. For instance, Jones & Warren (2010) show how the use of a MUVE (multi-user virtual environment) is proved to imply a remarkable increase of learning time for students. To face that, the authors consider a re-modeling of the 3-D environment’s time affordances through intelligent agents, aiming to guide learners’ behaviour and optimize their learning time. In parallel, they intend to reduce the time that teachers have to devote to repetitive kind of support.

28. Time affordances of Computer Learning Environments The notion of ‘ Affordances ’ has being highly contested over time (Oliver, 2006; Conole, 2011), but it is worth exploring it because it can shed light on ways in which ICTs shape learning time and collaborative work. McLoughlin (2007) defines affordances as “can do’s”, highlighting the meaning of ‘potentiality for action’ underlying this concept and characterising ICT tools and environments. Here we briefly consider the positions hold by Conole & Dyke (2004) and by Oliver (2006) and their implications for time affordances.

29. Time affordances of Computer Learning Environments Conole & Dyke (2004) build their taxonomy of ICTs affordances as socially-constructed accounts of technology and list a range of qualities attributable to ICTs, such as multimodality and non-linearity, reflection, immediacy. In their taxonomy, ‘time’ - as associated to a specific technology - appears to be mainly seen as a negative affordance (e.g. ‘time-consuming’ constraint) rather than a potentiality that can shape learner’s behaviour in creative ways. Oliver (2006) suggests an idea of affordances of ICT environments as referred to a literary analysis of technology , drawing from Bakthin’s work on analysis of literary genres. Technology should be studied as an evolving form of cultural artifact , in which social and historical production, as well as intentionality, are highlighted. In this perspective, ‘time affordances’ in ICTs can be intended in a more holistic way, as a dialectic dimension that is being intentionally co-constructed by actors in a specific educational context.

30. Time affordances of Computer Learning Environments In this line (even if independently with respect to Oliver’s discussion), Ligorio & Ritella (2009) build on the Bakthin’s notion of ‘chronotope’ to explore time affordances of an ICT-enhanced environment in a blended learning project. ‘ A chronotope is a genre of movement or pacing in the space that participants adopt over the temporal duration of an activity” (Ligorio & Ritella, 2009, p. 433). The authors utilize the lens of ‘chronotope’ to interpret the uniqueness of space/time dimension of the learning environment being constructed and used by participants. Adopting a musical metaphor, three different tempos (Adagio, Andante, Allegretto) are identified as occurring during the learning experience as a whole. Each tempo results as depending on features of tools being used, aims of the specific activities undertaken and different skills applied by participants.

31. Time affordances of Computer Learning Environments Two highlights as a provisional conclusion of these short notes: 1. The emerging complex digital landscape of new tools and environments induces further consideration of ICTs time affordances not as mere inherent qualities of individual technologies, but as enabling factors to be modeled by learning designers to actually fulfill time efficiency's expectations and to match learning and organizational needs of specific educational contexts. 2. Although further exploration and operationalisation of the interpretation of 'time affordances' within a literary analysis of technology and the notion of ‘chronotope’ are needed, both seem to constitute interesting holistic perspectives to interpret emerging networked learning environments (such as MOOCs, 'massive online open courses') and their time affordances.

32. Discussion Thanks for your time #timefactor #elearning #uoc #phd