Group awareness and regulation in computer-supported collaborative learning

Group awareness is of critical relevance for collaborative learning and interaction and is thus often referred to in CSCL research. However, the concept is only vaguely defined as some kind of understanding or perception of characteristics of learning partners or the collaborating group. Most CSCL research activities concerned with group awareness aim at modifying learners' awareness using so-called group awareness tools. However, there are much less attempts to measure group awareness and to conceptualize its formation. Thus, building on existing group awareness research, this article derives a conceptualization with six defining aspects of group awareness: (1) group awareness is cognitive, (2) group awareness is conscious, (3) group awareness is current, (4) group awareness is individual, (5) group awareness is social, and (6) group awareness is perceived as valid. Additionally, while it is often assumed that group awareness builds on self-regulatory skills, its role in regulating behavior and cognition within a social context is seldom explored. Thus, this article aims at defining and analyzing the concept of group awareness, specifying its relation to regulatory processes, and sketching possible research paths whilst building on, complementing, and informing tool-driven research

What interdependence can tell us about collaborative learning: a statistical and psychological perspective

When learning collaboratively, learners interact and communicate transactively. Interventions to foster collaborative learning frequently target such interactive processes and thus may drastically change how learners engage with and thus influence each other. One statistical phenomenon related to collaborative learning is the interdependence of data gained from learners collaborating. Often viewed as a mere statistical phenomenon, on a conceptual level, statistical interdependence is a similarity between learners mainly resulting from the mutual influence learners have on each other while collaborating and is thus closely related to collaborative practices. In this paper, we report data of an exemplary study (N = 82) to illustrate how information on interdependence and within- and between-dyad variance may add to data interpretation. The study examined how providing metacognitive group awareness information during collaboration affects individual learning outcomes. We found indications that the information fosters knowledge gain, but not confidence. Surprisingly, the data revealed different levels of interdependence between conditions, which led us to assume interdependence to be part of the treatment effect resulting from differential collaboration processes. We discuss reasons and implications of varying levels of statistical interdependence and their impact on inferential and descriptive statistics

Prompting and visualising monitoring outcomes: Guiding self-regulatory processes with confidence judgments

Sensible self-regulated study decisions are largely based on monitoring learning and using this information to control learning processes, but research has found that such processes may not be initiated automatically. To support learners, we adopted prompting and visualisation methods by asking learners to assign confidence ratings to learning tasks and visualising them during re-study, and tested the effects on metacognitive and cognitive measures in an experimental study (N = 95). Results show that prompting monitoring increased study efforts while visualising monitoring outcomes during learning focussed these efforts on uncertain answers. Due to low monitoring accuracy, metacognitively sensible regulation did not lead to cognitive learning gains. While the results support the idea of using visualisation techniques to implicitly guide self-regulated learning, more needs to be done to increase monitoring accuracy. Further, our study suggests that researchers should be aware of the effect that assessing confidence judgments has on subsequent learning behaviour

Analysing the Relationship Between Mental Load or Mental Effort and Metacomprehension Under Different Conditions of Multimedia Design

Cognitive load theory assumes effort may only lead to comprehension if the material-induced load leaves enough resources for learning processes. Therefore, multimedia materials should induce as little non-relevant load as possible. Metacognition research assumes that learners tap into their memory processes to generate a mental representation of their comprehension to regulate learning. However, when judging their comprehension, learners need to make inferences about actual understanding using cues such as their experienced mental load and effort during learning. Theoretical assumptions would assume both to affect understanding and its metacognitive representation (metacomprehension). However, the question remains how perceived effort and load are related to metacomprehension judgments while learning with multimedia learning material. Additionally, it remains unclear if this varies under different conditions of multimedia design. To better understand the relationship between perceived mental load and effort and comprehension and metacomprehension under different design conditions of multimedia material, we conducted a randomised between-subjects study (N = 156) varying the design of the learning material (text-picture integrated, split attention, active integration). Mediation analyses testing for both direct and indirect effects of mental load and effort on metacomprehension judgments showed various effects. Beyond indirect effects via comprehension, both mental load and effort were directly related to metacomprehension, however, this seems to vary under different conditions of multimedia design, at least for mental effort. As the direction of effect can only be theoretically assumed, but was not empirically tested, follow-up research needs to identify ways to manipulate effort and load perceptions without tinkering with metacognitive processes directly. Despite the limitations due to the correlative design, this research has implications for our understanding of cognitive and metacognitive processes during learning with multimedia

Assumptions and confidence of others: the impact of socio-cognitive information on metacognitive self-regulation

Self-regulated learning rarely happens in isolation and although there is a wide range of evidence that socio-cognitive information may impact decision making and learning, its role in metacognitive self-regulation remains understudied. Thus, we investigated how socio-cognitive information on assumptions and confidence in assumptions of an unknown other in a learning setting affects (1) changes in assumptions (i.e., convergence towards other), (2) perception of the other’s competence, and (3) the search for information (i.e., metacognitive and conflict-based regulation). In our empirical study, N = 60 students first read texts, then judged statements as being true or false and stated their confidence in these assumptions on an integrated confidence/answer scale, were then confronted with bogus information on the supposed answers of another learner (computer generated), and were then asked to (1) re-state their assumptions including confidence judgment, (2) judge the other’s competence, and (3) decide what statements they wanted additional information on. Results showed that learners (1) converged towards the other learner, (2) judged the other’s competence in accordance with the other’s stated confidence, and (3) regulated their learning based on their own (adjusted) confidence rather than on the presence or absence of socio-cognitive conflicts. This suggests that socio-cognitive information can affect how learners metacognitively evaluate own assumptions and thus impact self-regulatory processes, but also that confidence of others affects their perceived competence. Although the direct impact of socio-cognitive conflicts on regulatory processes remains unclear, this study fosters our understanding of self-regulated learning processes within social contexts

Understanding students’ academic help-seeking on digital devices – a qualitative analysis

Undergraduate students are expected to regulate their learning processes and overcome knowledge-related obstacles. Academic help-seeking (HS) is a social strategy to acquire missing information or explanations. As mobile devices are a popular means for communication between students, services on those devices are of interest for computer-mediated academic HS. The goal of the presented study is to determine requirements for the design of digital services that support asking for and receiving help. The article presents students’ perspectives on the knowledge-related obstacles that cause them to seek help through computer-mediated communication via mobile devices. Moreover, it presents respondents’ perceived inhibitions about asking peers for help. Finally, the perceived technical drawbacks of popular services are outlined. Data acquired from N = 59 semi-structured interviews were analyzed using qualitative content analysis. The students reported that they experience knowledge-related obstacles while working on assignments and that they avoid HS when they are worried about social humiliation. They also reported that a messenger service was used most frequently for HS. The results are valuable for designers and practitioners in the field of computer-mediated academic HS

The Cognitive-Affective-Social Theory of Learning in digital Environments (CASTLE)

For a long time, research on individuals learning in digital environments was primarily based on cognitive-oriented theories. This paper aims at providing evidence that social processes affect individual learning with digital materials. Based on these theories and empirical results, a social-processes-augmented theory is suggested: the Cognitive-Affective-Social Theory of Learning in digital Environments (CASTLE). This CASTLE postulates that social cues in digital materials activate social schemata in learners leading to enhanced (para-)social, motivational, emotional, and metacognitive processes. To substantiate this theory, socio-cognitive theories are used, which predict social influences on learning with digital materials. Besides, previous empirical findings are presented assuming that with a rising number of social cues in digital materials, the influence of social processes increases. Finally, consequences regarding the design of digital learning media are discussed

(Over)Trusting AI Recommendations: How System and Person Variables Affect Dimensions of Complacency

Over-trusting AI systems can lead to complacency and decision errors. However, human and system variables may affect complacency and it is important to understand their interplay for HCI. In our experiment, 90 participants were confronted with traffic route problems guided by AI recommendations and thereby assigned to either a transparent system providing reasons for recommendations or a non-transparent system. We found transparent systems to lower the potential to alleviate workload (albeit not to neglect monitoring), but to simultaneously foster actual complacent behavior. On the contrary, we found performance expectancy to foster the potential to alleviate workload, but not complacent behavior. Interaction analyses showed that effects of performance expectancy depend on system transparency. This contributes to our understanding how system- and person-related variables interact in affecting complacency and stresses the differences between dimensions of complacency and the need for carefully considering transparency and performance expectancy in AI research and design