Conference PaperPDF Available

Collaborative learning in Facebook: Can argument structure facilitate academic opinion change? Argumentative Knowledge Construction in SNS


Abstract and Figures

Social networking services (SNS), such as Facebook, are an increasingly important platform for computer supported collaborative learning (CSCL). However, little is known about whether and how academic opinion change and argumentative knowledge construction (AKC) can be facilitated in SNS. Existing argumentation practice in informal SNS discussions typically lacks elaboration and argumentative quality. We investigate the potential benefits of argument structure provided through individual computer-supported argument diagramming to foster academically sound opinions in the context of Facebook. In a quasi-experimental lab study, we found evidence of academic opinion change along with correlations of opinion change with knowledge gains.
Content may be subject to copyright.
Collaborative learning in Facebook: Can argument structure
facilitate academic opinion change?
Dimitra Tsovaltzi+, Armin Weinberger+, Oliver Scheuer^, Toby Dragon^,
Bruce M. McLaren^#
+Educational Technology, Saarland University, Saarbrücken, Germany, P.O. Box 151150
^CeLTech, Saarland University, Saarbrücken, Germany
#Carnegie Mellon University, Pittsburgh, PA, USA
Abstract: Social networking services (SNS), such as Facebook, are an increasingly important
platform for computer supported collaborative learning (CSCL). However, little is known
about whether and how academic opinion change and argumentative knowledge construction
(AKC) can be facilitated in SNS. Existing argumentation practice in informal SNS discussions
typically lacks elaboration and argumentative quality. We investigate the potential benefits of
argument structure provided through individual computer-supported argument diagramming
to foster academically sound opinions in the context of Facebook. In a quasi-experimental lab
study, we found evidence of academic opinion change along with correlations of opinion
change with knowledge gains.
Argumentative Knowledge Construction in SNS
Social networking services (SNS), such as Facebook, Twitter, Google+ etc., are rapidly growing communication
platforms. SNS provide easy platform-independent access and almost unrestricted interactivity for sharing ideas
and opinions, and may therefore be conducive to argumentative knowledge construction (AKC; Weinberger &
Fischer, 2006). AKC is the deliberate practice of elaborating learning material by constructing formally and
semantically sound arguments with the goal of gaining argumentative and domain knowledge. Argument
structure provided through individual argument diagramming is among the most prominent approaches to foster
AKC in CSCL environments (Scheuer et al, 2010). However, there is little known about the extent these
approaches can be applied to learning in SNS (McLoughin, & Lee, 2010; Tsovaltzi et al, 2012).
Current argumentation practice in informal SNS discussions lacks argumentative quality. Elaboration,
evidence testing, and the evaluation of new knowledge are rare (Kanuka, & Anderson, 1998). This may not be
surprising, since SNS were created for interactions at the personal level with users typically airing private
opinions. However, academic opinions, i.e. opinions about academic and school subject matters are also shared,
and potentially formed, through SNS (Roblyer, McDaniel, Webb, Herman, & Witty, 2010). Existing studies
show that purposeful use of social media can support information sharing, communication and collaboration
(Dabner, 2011), as well as learning (Laru, Näykki, & Järvelä, 2011). Yet, there is little systematic research on
the educational potential of SNS for academic opinion change or formation, and the facilitation of learning.
Research results learning suggest that argumentative elaboration can promote individual knowledge
construction, and can greatly benefit from additional support through scripting, i.e. socio-cognitive structures
that specify what learners are to do in collaborative learning scenarios (e.g. Baker & Lund, 1997; Weinberger,
Stegmann & Fischer, 2010). Learners, for instance, can be prompted to provide support or counterarguments for
their claims. This can help them elaborate the task, gain argumentative knowledge, understand multiple
perspectives, and promote knowledge convergence (Weinberger et al., 2010). An alternative way to script
learners is to let them first work on a task individually and then compare and combine their individual solutions
(e.g., Weinberger, 2011; Asterhan & Schwarz, 2007). Such approaches may prevent process losses of
simultaneously following diverse instructions, also characterized as over-scripting (Dillenbourg, 2002), which
can hinder AKC. Moreover, learners in online discussions often dismiss conflicting opinions and inconsistencies
rather than try to resolve them. Raising awareness of opinion conflict is one way to foster critical argumentative
elaboration during collaboration and take advantage of the dialogic potential of SNS (Bodemer, 2011).
In this paper, we investigate the potential benefits of argument structure provided through individual
computer-supported argument diagramming for academic opinion change in Facebook and its influence on
learning, compared to standard SNS discussions. We hypothesize that collaborators will resolve opinion
conflicts productively by building on sound argumentation and attain higher knowledge gains after individual
argument preparation as opposed to no individual preparation (Darnon et al, 2006). Our hypotheses are:
H1: Argument structure provided before SNS discussions will foster more academic opinion change than
standard SNS discussions.
H2: Opinion change will correlate with knowledge gains.
To test our hypotheses, we conducted a quasi-experimental lab study. We compared two conditions: argument
structure (ArgStr), which included individual construction of computer supported argument diagrams prior to
the collaborative discussion in Facebook, vs. no argument structure (NoArgStr), which included collaborative
discussion in Facebook only. The participants were randomly assigned to condition.
Forty (40) students at a German university ten dyads per condition took part in the study. Dyads
were chosen to maximize conflict on ethical aspects of the discussion topic (behaviorism in the classroom)
based on a questionnaire (see Section 2.2). Socio-demographic data, reported on an 1-5 Likert scale and
analyzed with the MannWhitney-U-Test, showed no significant differences between conditions in frequency of
SNS use, purpose of Facebook use (e.g., social contact and information exchange), ambiguity tolerance, interest
or prior knowledge, self-assessed domain knowledge, and familiarity with SNS and computer.
Figure 1. Abbreviated example of argument representation in LASAD
Due to privacy concerns, data collection for the experiment was done through specially created Facebook
accounts. To maintain the effect of opinion conflict awareness, which is native in Facebook, we posted strong
statements on behaviorism along two dimensions (effectiveness and ethics of behavioristic principles) and asked
participants in dyads to use the “like” button to indicate agreement with these statements. An example statement
on the ethical aspect is “The free will of a child must be facilitated at all costs.”
Students in the argument structure condition used the web-based system, LASAD, to create individual
argument diagrams (Loll, Pinkwart, Scheuer, & McLaren, 2012; see Fig. 1). Two types of boxes were available,
one to represent "claims" and the other to represent "evidence". Students could choose from a dropdown menu
whether (a) claims relate to the "effectiveness" or "ethics" of Behaviorism as a teaching method, and (b)
whether evidence was based on "scientific results," "examples," or "everyday knowledge". Boxes could be
related to one another through color-coded arrows, which indicated "support" (green arrows) or "opposition"
(red arrows). The diagrams aimed at helping students to construct arguments for and against Behaviorism as a
teaching method, contemplate the validity of arguments, as well as share and discuss the related evidence.
All students took an online pretest prior to the intervention in the Lab and a posttest. They also briefly
read an essay on Behaviorism that could be used as reference during the intervention. The duration of the
intervention was 55 minutes. NoArgStr used the entire time discussing on Facebook and trying to reach an
agreement on the topic "Should behavioristic principles be applied in the classroom?" ArgStr used the first 25
minutes prior to the Facebook discussion to individually create an argument diagram with LASAD on the topic.
Opinion Conflict, Formation and Change
Opinion conflict, used to group dyads, was measured with a questionnaire in which participants had to state their
agreement with statements on the effectiveness and ethical aspects of the principles of behaviorism for learning
on a 5-point Likert scale. A statement on effectiveness, translated from the German original, is “Behaviorism
can be applied with learning success on simple tasks”, and on ethics, It is potentially wrong to use negative
reinforcement on kids.” To analyze opinion formation independent of the direction of opinion change (that is,
opinions becoming more or less favorable), we used a t-test of the absolute difference between the mean pre-
statement score and the mean post-statement score of each participant.
Knowledge Test
Our knowledge test comprised twenty-four multiple-choice and two open questions (“Name some weak/strong
points of behaviorism.”), evaluated by two raters. The inter-rater-reliability was substantial for pre and posttest
for the first question, Cohen’s kpre =.86; Cohen’s kpost =.86, and moderate for the second question, Cohen’s kpre
51; Cohen’s kpost =.44. To compare the knowledge scores we used the GLM Univariate procedure.
Academic Opinion Formation and Change
Both conditions changed their overall opinion significantly, t(39)=8.84, p<.001, d=1.40, as well as on the two
dimensions, effectiveness, t(39)=8.10, p<.001, d=1.28; ethics, t(39)=9.04, p<.001, d=1.43. With respect to H1,
the influence of argument structuring on opinion change, the results showed that neither condition changed their
opinions more than the other between pre- and posttest, either for the overall opinion, F(1,38)=.09, p=.77, or for
the separate dimensions, ethics, F(1,38)=.17, p=.68, and effectiveness, F(1,38)=.84, p=.36. Since prior research
suggests that cognitive conflict is predictive of collaborative learning in the context of social media (Kanuka
&Anderson, 1998), we tested if the number of conflicts per statement would differ between conditions. Indeed,
an ANOVA showed neither a significant difference between conditions on the mean number of conflicts per
statement overall, F(1,16)=.99, p=.33, nor on ethical aspects vs. effectiveness separately, F(1,16)=1.93, p=.17.
To get a better idea of how these new opinions were formed between groups, we compared the
direction of opinion change from pre- to posttest between groups (Figure 2). Prior to the learning intervention,
ArgStr dyads judged Behaviorism as a teaching method more positively than NoArgStr: overall, F(1,38)=6.80,
p=.013, ηp2=.15; ethics, F(1,18)=5.63, p=.023, ηp2=.13; and effectiveness, F(1,18)=3.20, p=.08, ηp2=.08 (trend
only). The attitude of the two conditions changed after the intervention giving interaction effects for all scores.
NoArgStr dyads became less and ArgStr dyads more critical in their overall judgment, resulting in a strong
interaction, F(1,38)=9.70, p=.003, ηp2=.20. Both conditions evaluated ethical aspects of Behaviorism more
favorably between pre- and posttest, F(1,38)= 7.91, p=.008, ηp2=.17), but the ratings of the NoArgStr dyads
increased more than those of the ArgStr dyads, producing a significant interaction effect, F(1,38)=4.53, p=.04,
ηp2=.11. An even stronger interaction effect can be observed between pre- and posttest on effectiveness,
F(1,38)= 10.79, p=.002, ηp2=.20 (Fig. 3). Here, the ratings of NoArgStr dyads changed in favor of
Behaviorism’s effectiveness, whereas the ratings of ArgStr dyads became less favorable. A plausible reason for
the opinion change may be that conflict awareness helped partners in both conditions to transact on another’s
opinion. This active cognitive engagement with conflicting views may have destabilized their original opinions
and caused changes that are depicted in the strong interactions.
Domain Knowledge Gains
The comparison of the conditions in the pretest showed a significant difference in the pretest for the percentage
of correct answers, F(1,38)=18.59, p<.001, ηp2=.33. Both conditions did significantly better on the posttest than
the pretest, F(1,38) = 87.55, p<.001, ηp2=.70. The knowledge gains of the two conditions did not differ,
F(1,38)=.73, p=.399, ηp2=.02.
The opinion formation and change reported in the previous section is particularly interesting as it may
signify a potential for knowledge gain via a deeper processing of domain knowledge in SNS. This is one of the
biggest promises of ACK and of co-construction of knowledge. To test this possibility, we calculated
correlations between opinion change and knowledge gains. The correlation between overall opinion change of
both conditions together and the overall knowledge gains just missed being significant, r(40)=.31, p=.050.
Although this effect seems to confirm H2, a closer look shows that the correlation for both conditions together is
probably due to the very high correlation found for NoArgStr alone, r(20)=.54, p<.05, but not for ArgStr.
Figure 2. Opinion comparison: Overall, Effectiveness, Ethics
Pre Post
Pre Post
Pre Post
Despite the generally held opinion that Facebook is shallow and non-serious, we found evidence that it
can be used for academic opinion formation and change when sufficiently supported. We theorized that
argument structure as support for sound academic argumentation would favor academic opinion formation more
than standard SNS discussions when opinion conflict is highlighted. This did not prove to be the case.
Moreover, we could not establish a correlation between opinion change and knowledge gains for argument
structure. On the contrary, we found highly significant correlations between opinion change and knowledge
gains for the NoArgStr condition. A possible reason for these results could be the higher prior knowledge of the
NoArgStr condition, which may benefit opinion change in the context of AKC (Darnon et al., 2006). However,
it is worth investigating whether opinion conflict awareness is a stronger predictor of academic opinion change
and how argument support exactly interacts with such awareness.
Given the open and social character of SNS and the possibility to acquire new, unpredictable
knowledge and skills, such as openness to opinion change, assessment of learning in SNS needs to be redefined.
Traditional learning tests based on factual knowledge or problem solving skills do not capture the power of SNS
and remaining faithful to them can limit the effectiveness and restrict the potential of SNS as learning tools.
Asterhan, C.S.C. & Schwarz, B.B. (2007). The effects of monological and dialogical argumentation on concept
learning in evolutionary theory. Journal of Educational Psychology 99(3), 626639.
Baker, M. & Lund, K. (1997). Promoting reflective interactions in a CSCL environment. Journal of Computer
Assisted Learning 13, 175193.
Bodemer, D. (2011). Tacit guidance for collaborative multimedia learning. Computers in Human Behavior,
27(3), 10791086.
Dabner, N. (2011). “Breaking Ground” in the use of social media: A case study of a university earthquake
response to inform educational design with Facebook. The Internet and Higher Education, 15(1), 69
Darnon, C., Muller, D., Schrager, S.M., Pannuzzo, N., & Butera, F. (2006). Mastery and performance goals
predict epistemic and relational conflict regulation. Journal of Educational Psychology, 98(4), 766
Dillenbourg, P. (2002). Over-scripting CSCL: The risks of blending collaborative learning with instructional
design. In P.A. Kirschner (Ed.), Three worlds of CSCL: Can we support CSCL? (pp. 6191). Heerlen:
Open Universiteit Nederland.
Kanuka, H. & Anderson, T. (1998). Online Social Interchange, Discord, and Knowledge Construction. Journal
of Distance Education/Revue de l’enseignement à distance,13(1), 119.
Laru, J., Näykki, P., & Järvelä, S. (2011). Supporting small-group learning using multiple Web 2.0 tools: A case
study in the higher education context. The Internet and Higher Education, 15(1), 2938.
Loll, F., Pinkwart, N., Scheuer, O., & McLaren, B.M. (2012). How Tough Should It Be? Simplifying the
Development of Argumentation Systems using a Configurable Platform. In N. Pinkwart, & B.M.
McLaren (Eds.), Educational Technologies for Teaching Argumentation Skills, Bentham Science
Publishers, 169-197.
McLoughin, C. & Lee, M.J.W. (2010). Personalised and self regulated learning in the Web 2.0 era: International
exemplar of innovative pedagogy using social software. Australian Journal of Educational Technology,
26(1), 2843.
Roblyer, M.D., McDaniel, M., Webb, M., Herman, J., & Witty, J.V. (2010). Findings on Facebook in higher
education: A comparison of college faculty and student uses and perceptions of social networking sites.
The Internet and Higher Education, 13(3), 134140.
Scheuer, O., Loll, F., Pinkwart, N., & McLaren, B.M. (2010). Computer-supported argumentation: A review of
the state of the art. International Journal of Computer-Supported Collaborative Learning, 5(1), 43
Tsovaltzi, D., Weinberger, A., Scheuer, O., Dragon, T., & McLaren, B. (2012). Argument Diagrams in
Facebook: Facilitating the Formation of Scientifically Sound Opinions. In A. Ravenscroft, S.
Lindstaedt, C. Delgado Kloos, & D. Hernandéz-Leo (Eds.), 21st Century Learning for 21st Century
Skills, Proceedings of EC-TEL 2012, LNCS 7563 (p. 540). Berlin: Springer.
Weinberger, A. & Fischer, F. (2006). A framework to analyse argumentative knowledge construction in
computer-supported collaborative learning. Computers & Education, 46, 71-95.
Weinberger, A., Stegmann, K., & Fischer, F. (2010). Learning to argue online: Scripted groups surpass
individuals (unscripted groups do not). Computers in Human Behavior, 26(4), 506515.
Weinberger, A. (2011). Principles of transactive computer-supported collaboration scripts. Nordic Journal of
Digital Literacy, 6(3), 189202.
... etc. (Hrastinski, 2008;O'Neil et al., 2010), while in the last decade there has been a growing body of research exploring the role that popular social media platforms, such as Facebook, can play in collaborative learning. (Llorens & Capdeferro, 2011;Jumaat and Tasir, 2013;Tsovaltzi, Weinberger, Scheuer, Dragon, & McLaren, 2013;Prestridge, 2014;Mahmud & Wong, 2018). It is therefore evident that we still have a lot more to learn when it comes to quality elements of e-learning, which, despite having evolved, still remains largely unexplored (Wu, 2015;Esfijani, 2018). ...
The Hellenic Open University launched synchronous online group advisory meetings for the academic year 2016-17 through the Skype for Business videoconferencing platform. This chapter focuses on the extent to which interaction, immediacy, and collaborative learning are developed in this particular online learning environment, as well as on the skills required for an efficient adult e-tutor. Research conducted in 2019 has shown that learners scored high in terms of interaction, immediacy, and collaborative learning between each other and their tutor, especially when working in online workgroups, while the learning process was facilitated by immediate e-tutor feedback, which resolved queries, and the effective facilitation of the discussion. In terms of factors hindering the learning process, learners cited the lack of meaningful relationships with their peers as a leading οne, e-tutors pointed to technical problems, while both agreed on the inadequate use of communication and collaborative tools in an online environment.
... Walther & Parks, 2002), are more likely to be met with verbal aggressiveness, and no resolution seems to be accomplished in the vast majority of these exchanges. These results are somewhat contrary to those of Tsovaltzi et al. (2012Tsovaltzi et al. ( , 2013. It may be the case that naturally occurring arguments are perceived as less able to elicit collaborative learning, in which case arguing online needs a radical reframing. ...
This study explored how people argue on social-networking sites. Specifically, participants (N = 170) responded to open and closed-ended questions about the most recent argument they had engaged in on Facebook. Results of a content analysis of participants’ answers revealed individuals tended to argue mostly about public issues, in somewhat complex arguments that involved a median of six people and with about 30 comments exchanged. Individuals often pursued multiple goals, with persuasion and defending themselves or others also reported by some. Arguments tended to end without resolution, and most had no effects on arguers’ relationships; however, for 20% of the sample, arguments permanently damaged their relationships. Although the number of friends participants had did not have a substantial effect on their frequency of arguing, the frequency with which one’s friends argued on Facebook was positively related to one’s own arguing frequency. These results are interpreted in connection to argumentation and computer-mediated-communication literatures. Limitations of the study as well as directions for future research are also discussed.
... This is a general limitation acknowledged by Junco [13]. Actual quantitative studies include the work of Tsovaltzi et al., who proposed the use of specially created Facebook accounts for having access to the actual data in Facebook [18]. In a later study, Nvivo and NCapture were used to download data published on a Facebook Group created on purpose for the experiment [19]. ...
... Analyze, discuss, and solve problem case related to given domains. PS [56] -To investigate the potential benefits of argument structure provided through individual computer- supported argument diagramming to foster academically sound opinions in the context of Facebook. ...
Conference Paper
Full-text available
In this era of rapid development of Information and Communication Technology (ICT), online collaborative and social learning has been seen as one of the ways to encourage students' critical thinking skills. Past studies have proven that students' critical thinking skills were shown significantly when it is done socially and collaboratively amongst peers. Previous researches also stated that cooperative teams achieve at higher levels of thought and preserve information longer than learners who work quietly as individuals. In addition, working in a collaborative environment also involves processes of evidence and argumentation. Argumentation refers to making convincing claims backed up by sound evidence and broad understanding of various aspects of an issue. Argumentation learning activities can serve as an effective mechanism of spreading of knowledge through a network of exchanges in small groups. However, argumentative knowledge construction (AKC) in social collaborative learning environments is often insubstantial. So, does an argumentative learning activity in social collaborative learning environment truly result in enhancing students' higher order thinking skills (HOTs) and knowledge construction? Thus, the purpose of this paper is to discuss a meta-analysis on thinking skills that lead to the need for social collaborative learning and argumentative knowledge construction process towards enhancing students' HOTs.
Full-text available
blockquote> Research findings in recent years provide compelling evidence of the importance of encouraging student control over the learning process as a whole. The socially based tools and technologies of the Web 2.0 movement are capable of supporting informal conversation, reflexive dialogue and collaborative content generation, enabling access to a wide raft of ideas and representations. Used appropriately, these tools can shift control to the learner, through promoting learner agency, autonomy and engagement in social networks that straddle multiple real and virtual learning spaces independent of physical, geographic, institutional and organisational boundaries. As argued in this article, however, in order for self-regulated learning to come to fruition, students need not only to be able to choose and personalise what tools and content are available, but also to have access to the necessary scaffolding to support their learning. Emerging practices with social computing technologies, a number of examples of which are showcased in this article, signal the need for pedagogies that are more personal, social and participatory. The authors conclude with a discussion of some of the key implications for practice, including an outline of the current challenges faced by tertiary educators. </p
Full-text available
Teaching to argue is challenging. Classic face-to-face approaches do not scale up for large groups due to resource limitations (teacher time), but have shown to be effective. As a consequence, there have been attempts to convey argumentation skills via educational software. Even though some of these systems have shown their suitability in their original domains of application, the systems typically do not generalize – there has been little carry over to other domains. This chapter reviews existing approaches, their technological strengths and weaknesses, and proposes a generic architecture to overcome the latter. Based on this architecture, the LASAD (Learning to Argue – Generalized Support Across Domains) framework has been developed. The goal of this framework is to simplify the development of argumentation systems based on some well-defined configurations. In this chapter, we describe the flexibility of the LASAD framework and demonstrate how it can be configured to emulate the existing argumentation systems Belvedere and LARGO.
Conference Paper
Full-text available
Students use Facebook to organize their classroom experiences [1], but hardly to share and form opinions on subject matters. We explore the benefits of argument diagrams for the formation of scientific opinion on behaviorism in Facebook. We aim at raising awareness of opinion conflict and structuring the argumentation with scripts [2]. A lab study with University students (ten dyads per condition) compared the in-fluence of argument structuring (students built individual argument diagrams before discussing in Facebook) vs. no argument structuring (only Facebook discussion) on opinion formation, measured through opinion change. The argumentation script was implemented in the web-based system LASAD to support sound argumentation [3]. Fig. 1. View of LASAD diagram Facebook discussions and conflict awareness led students of both conditions to change their opinions, t(39)=8.84, p<.001. Evidence suggests a connection between opinion change and the number of conflicts in a discussion. Together with a high correlation for no argument structuring between opinion change and knowledge gains, r(20)=.54, p<.05, the results suggest benefits of raising awareness of opinion conflicts in Facebook to facilitate scientific opinion formation and change. References.
Full-text available
In this study, the effects of argumentation-eliciting interventions on conceptual understanding in evolution were investigated. Two experiments were conducted: In the 1st, 76 undergraduates were randomly assigned to dyads to collaboratively solve and answer items on evolution; half of them were instructed to conduct an argumentative discussion, whereas control dyads were only asked to collaborate. In the 2nd experiment, 42 singletons participated in 1 of 2 conditions: Experimental students engaged in monological argumentation on their own solution and a confederate's solution in response to prompts read by the confederate, whereas in the control condition they merely shared their solutions. Conceptual gains were assessed on immediate and delayed posttests. In both experiments, students in the argumentative conditions showed larger learning gains on the delayed posttest than control students. Students in argumentative conditions were able to preserve gains that were obtained immediately following the intervention, whereas control participants either lost immediate gains (dialogical condition) or did not improve their conceptual understanding at any time (monological condition). (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Full-text available
The present research examines whether mastery and performance goals predict different ways of reacting to a sociocognitive conflict with another person over materials to be learned, an issue not yet addressed by the achievement goal literature. Results from 2 studies showed that mastery goals predicted epistemic conflict regulation (a conflict regulation strategy focused on the attempt to integrate both points of view), whereas performance goals predicted relational conflict regulation (a conflict regulation strategy focused on the evaluation and affirmation of self-competence). Study 1 shows these links via direct self-report measures of conflict regulation. Study 2 shows the same links using the amount of competence reported for the self and for the other as subtle measures of conflict regulation.
Parts of the classroom of the future may be built online allowing for computer-supported collaborative learning (CSCL). A central challenge in CSCL is a lack of transactivity, i.e., learners have problems building on the reasoning of their peers. A means of fostering CSCL are scripts that specify, sequence, and distribute roles and activities among a group of (online) learners. This article identifies five instructional design principles that explain script effects and inform script design: 1) regulation of learning activities; 2) complementary procedural knowledge; 3) process-oriented instruction; 4) substitution of coordination efforts; and 5) awareness induction.
On September 4 2010, a massive 7.1 magnitude earthquake struck the Canterbury region in the South Island of New Zealand. The response from the University of Canterbury was immediate and carefully co-ordinated, with the university's web-based environment and a responsive site developed on the social media platform ‘Facebook’ becoming prominent sources of support for many months. This case study illustrates how the university effectively utilised these environments and their impact within the wider university community. Case study methodology draws upon literature from the fields of social media, social network communities and crisis informatics. The findings propose that social media can effectively support information sharing, communication and collaboration in higher education contexts, in particular in times of crisis, but suggest there needs to be a defined purpose to integrate these within an institution's communications strategy given the resource implications and range of social media already used by students.
In this single-case study, small groups of learners were supported by use of multiple social software tools and face-to-face activities in the context of higher education. The aim of the study was to explore how designed learning activities contribute to students' learning outcomes by studying probabilistic dependencies between the variables. Explorative Bayesian classification analysis revealed that the best predictors of good learning outcomes were wiki-related activities. According to the Bayesian dependency model, students who were active in conceptualizing issues by taking photos were also active blog reflectors and collaborative knowledge builders in their group. In general, the results indicated that interaction between individual and collective actions likely increased individual knowledge acquisition during the course.
Engaging in reflective activities in interaction, such as explaining, justifying and evaluating problem solutions, has been shown to be potentially productive for learning. This paper addresses the problem of how these activities may be promoted in the context of computer-mediated communication during a modelling task in physics. The design principles of two different communication interfaces are presented. The first allows free text to be exchanged, and the second structures the interaction by providing a restricted set of communicative possibilities. Comparative analyses of interaction corpora produced with the two communication interfaces are then described. The analyses show that use of the second structured interface in performing the problem-solving task is feasible for students, and that it promotes a task-focussed and reflective interaction. In conclusion the different resources provided by different media and the relative degrees of effort that their use requires are discussed.