Introduction Notions of context in TEL tend to focus on cultural concerns. When discussing the “instrumentalising” of learning contexts, for example, the STELLAR Vision and Strategy Statement (Sutherland & Joubert, 2009, p.7) suggests that “technologies for learning should be designed to take into account the ways in which the settings where they will be used are mediated by cultural context” so as to “provide learners with novel experiences by exposing them to a wider range of contexts than was previously possible”. This document outlines relevant work on Learning Spaces and points to the need for a “spatial turn” in TEL discussions of context for two reasons: (1)TEL designers need an increased awareness of the physical settings in which their systems will be deployed and (2) this approach can help to augment our notions of what context actually is.

A Spatial Turn Context is a notoriously contentious topic. From a TEL perspective, Sharples (2010) has provided a representational model of Context (p.4) as a historical process which can be understood as an interweaving of ‘movies’ of people interacting with settings and artefacts over time (p.6). ‘Context states’ comprise the scenes in the movie, from which ‘Context Substates’ of relevant elements can be abstracted. In earlier work, a Context Engine was proposed to select more relevant elements from the context state and make them available for learners through mobile devices (Lonsdale et al., 2004). This view is partly compatible with prior conceptions of context from HCI (Dourish, 2004) in that context is seen as personally constructed rather than as a container. But where Dourish (2004) argues that “representational” and “interactional” views of context are opposed (p.22), this work aims to explore how a (representational) model of contextual relevance can support the (interactional) “process by which context is continually manifest, defined, negotiated and shared” (p.26). This process of context construction will involve the learner navigating both external and internal influences (Jacob, 2009), where external influences include “the artifacts, the people, and the particular setting(s) associated with a given situation, task or activity” (p.92). In this view, Learning Spaces would be settings, which both encompass people and artifacts and, in turn, are created by them (Laegran, 2009). Adopting an Activity Theory perspective reminds us that this relationship between people and artifacts is asymmetrical, since only people have “the ability and the need to act” (Kaptelinin & Nardi, 2006, p.33), that is the internal influences which affect context creation.

The Learning Spaces concept itself has increasingly come to be understood through a social lens. Learning Spaces literature used to be about producing design specifications and descriptions of “innovative spaces”, taking inspiration from “basic research about space, place, perception and learning” (Van Note Chism, 2002, p.8). But more recently such work has become more socially (and sociologically) conscious. Building on work by Lefebvre (1974/1991), for example, Boys (2011, p.81) proposes that we examine space as a dynamic between: social and spatial practices (“ordinary” routines of educational communities of practice); designed transformations of existing spatial practices (established repertoires for transformations); and spaces in-between (our individual understandings of our social-spatial practices).

Recent work on students’ spatial practices in a technology-rich University library (Crook and Mitchell, in press) has highlighted the importance of developing a “nuanced” view of how social interaction occurs to support learning, since such interactions occur along a spectrum from intense collaborative problem solving — the subject of much study within the TEL/CSCW literature — through more intermittent exchanges and serendipitous encounters and on to an “ambient sociality” where individual study occurs within an atmosphere which seems sociable(or convivial) to learners. Interestingly from a TEL viewpoint, Crook and Mitchell (ibid) note that much physical collaboration occurs in ways reminiscent of online interactions within Web 2.0 social networking sites, i.e. loosely-coupled, improvised and intermittent as well as the close and intense encounters which are much better represented within TEL literature.

In documenting the use of an innovative technology-rich Learning Space used for more formal learning, Bligh & Lorenz (2010, p.16) reason that whereas more traditional spaces can utilise socio-spatial convention as a guide for action, innovative spaces which break these conventions must be more explicit about how they are to be used. Thus creating innovative learning spaces must be associated with documenting innovative models of pedagogy which can occur there. Bligh & Lorenz (2010) articulate how they believe “multiple perspective learning” can work within a Multi-Display Learning Space. Bligh & Sharples (2010) make the link between TEL and Multi-Display Learning Spaces more explicit, drawing on Ainsworth’s (2006) DeFT framework to show how multiple perspective learning can be seen as a co-located, real-time orchestration of the principles of learning from Multiple External Representations which have been derived from work with online tutoring systems.
While this work ostensibly focusses on the ability of Learning Spaces to support the visual aspects of interaction, it must be acknowledged that writers within the architecture literature have proposed that it is precisely the dominance of the visual in architectural design (or “ocularcentrism”) which is responsible for the sterility of much contemporary architecture, and that re-focussing on the experience of the whole body (Pallasmaa, 1995/2005) can result in better spatial experiences and understandings (cf. spaces in-between above). Work on Multi-Display Learning Spaces answers this challenge by emphasising how the space supports movement (Bligh & Lorenz, 2010) and the construction of disciplinary argument (Bligh & Sharples, 2010), but understanding the limitations of the visual sense in physical interactions is nonetheless useful more broadly in avoiding situations where the visual aesthetic becomes an end in itself, devoid of the contextualisation provided by activity and the physical situation.

Studying the relations between socio-spatial practices, design and individual understandings can also be informed by work which has examined the evaluation of physical Learning Spaces. Bligh & Pearshouse (in press) stress that such work highlights significant tensions as spaces are valued in different ways by different people. Spaces might be assessed on whether they are (a) in demand, (b) change learning outcomes, (c) satisfy their occupants, (d) enable scenario provision, (e) support spatial activities, (f) fit into a wider ecology of provision or (e) enhance institutional brand. Student satisfaction with space often follows a deficit model (i.e. it is only mentioned as relevant when students are dissatisfied and believe that a problem needs to be addressed), which also needs to be understood by those working with TEL. Perceived relevance (or focus of attention) is not uniformly a good thing. Meanwhile the relationship in this model between evaluating scenario provision (ensuring that space is appropriate for anticipated activities) and evaluating support for spatial activities (systematic observation of spatial practice) highlights how complex the relationship is between design, physical manifestations of action which can be observed and (phenomenological) personal understanding. Bligh & Pearshouse (in press) also highlight how space evaluation is an essentially political act which balances the above values against institutional and cultural constraints, implying that we must view evaluation reports themselves critically when we wish to inform design or policy.

Finally, we want to highlight that TEL can benefit from hindsight of Learning Spaces’ history of deriving design from “evidence” which amounts to little more than word association. Boys (2011, p.18) highlights the examples of informality and flexibility, where understanding that learning is mobile and flexible and is often informal was taken to mean that Learning Spaces should be inherently ‘flexible’ (i.e. have moveable furniture) and ‘informal’ (adding beanbags, or mimicking the spatial repertoires of cafes). Boys (ibid) refers to these solutions as under-theorised, common-sense and obvious. More nuanced views of these issues can be found: on flexibility in the work of Goodyear (2008) who considers the advantages and drawbacks of time-space flexibility at macro, meso and micro scales; and on formality in the work of Sutherland & Sutherland (2010), who note that spaces can be better viewed as diverse and positioned along a spectrum from formal, through semi-formal and semi-informal and onwards to informal spaces, based upon the roles of teachers in activities occupying the space. Thus work on Learning Spaces can help to highlight for TEL that ‘obvious’ solutions may not always be wrong, but that in determining applicability there is no substitute for understanding activity and context when making design decisions.

Emerging aspects of research

• How can Learning Spaces be designed to enable appropriate context for learning? Continuing Sharples’ (2010) movie metaphor, how can we set up scenes for learning and what would be the role of props and actors in these scenes?


• How can we design new buildings (and, for Higher Education) campuses to create new context opportunities for learning?


• What is the relationship between technologies for learning and Learning Spaces? Can space be viewed as a ‘technology’ for learning within interaction design?


• What does it mean to design to provide a convivial learning environment? Can we create ‘tools for conviviality’?


• How can spatial action, perhaps within a Community of Practice, be understood as related to space? What elements of this relationship are poorly represented by affordances and ergonomics arguments (Goodyear, 2008)?


• Can we construct models of the relationship between design and various forms of evaluation (measurement based, phenomenological) to form a better understanding of how context is constructed?


• How does a contextual view of Learning Spaces challenge traditional design and evaluation practices?

for references, please download pdf version of TEL note

The use of digital games for education is an hot issue, since computer games are increasingly regarded as emerging technologies having an high potential to foster learning and also, in some cases, to improve school and academic achievement (de Freitas, 2006; Mitchell & Savill-Smith, 2004). Such general potentialities are presently investigated by a number of significant research studies according to different perspectives and contexts. These studies consider, for example, the relationships that are established among types of games, learning objectives to be met and the learning population to be addressed, that is, they take into account which kind of games better serve the scope of fulfilling specific learning objectives and how this can be done in specific learning contexts and with specific target populations (Pivec, 2007).

In this framework, a group of researchers at the Institute of Educational Technology of the Italian National Research Council (ITD-CNR) is carrying out research projects focusing on mind games and their use to develop logical and reasoning abilities.

As a matter of fact, many authors recognize that the educational use of digital games has a significant impact on children’s cognitive skills (Whitebread 1997; Amory et al. 1999; Jenkins 2002; Mc Farlane et al. 2002; Kiili 2007), nevertheless, mind games, which are also called puzzles or brainteasers (Mitchell and Savill Smith 2004, Prensky 2001; Schiffler 2006), are not frequently studied from the point of view of learning outcomes (Facer et al. 2007) and few studies investigate the specific cognitive abilities they cover (Milovanovic et al. 2009, Shih & Su, 2008).

ITD-CNR researchers have carried out long term in-field experiments in primary school classes with the main aim of promoting the development of strategic and reasoning abilities in young students by means of digital mind games. To this purpose, the cognitive abilities involved in such games were investigated (Bottino & Ott, 2006) and the main design and interface features that make them more or less suitable to the intended use were examined (Bottino et al., 2009). The conducted experiments have highlighted the pedagogical potential of mind games to support and foster reasoning skills and have also shown that, under certain conditions, their use may also affect students’ performance in curricular subjects such as mathematics (Bottino et al., 2007).

Some other issues related to the educational use of digital mind games have also been investigated, among which their potential to influence students’ engagement and motivation (Ott and Tavella, 2010) and their ability to sustain the development of student creativity (Ott and Pozzi, 2011).

More recently, a specific research project funded by the Italian Ministry of Education, the LOGIVALI project, has been carried out to verify whether and to what extent a selected number of digital mind games could be used to investigate the students’ possess of a set identified reasoning skills (Bottino et al., 2010). Within the project, a norm-referenced test was designed and produced. In order to perform the validation and standardization of this test, a large- scale in-field experiment, involving more than 50 teachers and 500 primary school students (grades 4th and 5th) was carried out. The project demonstrated the suitability of mind games to assess relevant reasoning abilities as far as the target population (pupils’ age level 8-10) is concerned. Such abilities are important because they can be considered as “transversal” to a great number of learning tasks and therefore can highly influence students’ global academic achievement (Rohde and Thompson, 2007; Robertson and Miller 2009).

for references, please download pdf version of TEL note

The research problem is about the models, design, implementation and evaluation of adapted epistemic feedback in the interaction cycle between the learning situation and the student.

The adapted "problématique" is related to how to produce a feedback which is adjusted to the context: user, learning situation, domain, didactical constrains, etc..;

The epistemic "problématique" is related to how to take into account the knowledge coming from considered models: user, situation, teacher, domain, etc..., in order to calculate and produce the feedback.

The European project fLL (Language Technologies for Lifelong Learning, FP7, ICT-STREP) produces a deliverable about the state of art of the feedback notion in Educational science. In this deliverable, the overview made by Mory (2004, p. 745) is showed: “most educational researchers consider the term “feedback” in the context of instruction. Feedback has been widely perceived as an important component of general systems operations and may be viewed under a variety of settings (Kowitz&Smith, 1985, 1987). In the purely instructional sense, feedback can be said to describe any communication or procedure given to inform a learner of the accuracy of a response, usually to an instructional question (Carter, 1984; Cohen, 1985; Kulhavy, 1977; Sales, 1993). This type of feedback acts as one of the events of instruction described by Gagné (1985) and usually follows some type of practice task. More broadly, feedback allows the comparison of actual performance with some set standard of performance (Johnson & Johnson, 1993). In technology-assisted instruction, it is information presented to the learner after any input with the purpose of shaping the perceptions of the learner (Sales, 1993). Information presented via feedback in instruction might include not only answer correctness, but other information such as precision, timeliness, learning guidance, motivational messages, lesson sequence advisement, critical comparisons, and learning focus (Hoska, 1993; Sales, 1993). In fact, Wager and Wager (1985) refer to feedback in computer-based instruction as being any message or display that the computer presents to the learner after a response.

The models often are cognitive-based and detail in several tiers how feedback can be designed, delivered and understood. The classifications are based on the feedback nature or form, on the feedback degree of complexity, and on the feedback objectives". Trausan-Matu et al. (2008, p. 17)".

Besides, but also in educational Science, Shute (2007, p. 10) propose a classification of feedback and shows the difficulty to decide what is the best feedback for learning: "For instance, the positive effects of immediate feedback can be seen as facilitating the decision or motivation to practice and providing the explicit association of outcomes to causes. On the downside, immediate feedback may lead to reliance on information that is not available during transfer, and it also may promote less careful or mindful behavior. […] A similar argument could be made for delayed feedback effects on learning. For example, on the positive side, delayed feedback may encourage learners’ engagement in active cognitive and metacognitive processing […]. But on the negative side, delaying feedback for struggling and less motivated learners may prove to be frustrating and detrimental to their knowledge and skill acquisition”.

Thus, it is necessary to define and model the elements to be considered for produce adapted epistemic feedback. We propose to consider the domain model, the student model and the learning situations which can be orchestrated by scenarios.

In our approach, the assessment will be an evaluation of the coherence of the user’s solutions according to the context of the problem and not necessarily based on its correctness or its similarity to the expert’s solution, like most of the intelligent tutoring systems (Woolf, 2009). In addition, the assessment of user’s knowledge by the system is uncertain. It is not possible to know exactly the user knowledge, but we can deduce it with a degree of certainty from her/his actions (Conati, Gertner, & VanLehn, 2002). For us, one of the challenges is to propose computer tools based on educational and cognitive science theories to achieve adequate assessment and to organize this kind of feedback (Lajoie, Faremo, & Wiseman, 2001).

for references, please download pdf version of TEL note