Ard W. Lazonder

Co-Lab: research and development of an online learning environment for collaborative scientific discovery learning

There are many design challenges that must be addressed in the development of collaborative scientific discovery learning environments. This contribution presents an overview of how these challenges were addressed within Co-Lab, a collaborative learning environment in which groups of learners can experiment through simulations and remote laboratories, and express acquired understanding in a runnable computer model. Co-Labs architecture is introduced and explicated from the perspective of addressing typical problem areas for students within collaborative discovery learning. From this view the processes of collaboration, inquiry, and modeling are presented with a description of how they have been supported in the past and how they are supported within Co-Labs design and tools. Finally, a research agenda is proposed for collaborative discovery learning with the Co-Lab environment.

Trends and issues of regulative support use during inquiry learning: Patterns from three studies

This paper looks across three experimental studies that examined supports designed to assist high-school students (age 15-19) with cognitive regulation of their physics inquiry learning efforts in a technology-enhanced learning environment called Co-Lab. Cognitive regulation involves the recursive processes of planning, monitoring, and evaluation during learning, and is generally thought to enhance learning gains for students. The research synthesis described in this paper examined the usage effects of a support tool called the process coordinator (PC) on learning outcomes. This tool incorporated goal-lists, hints, prompts, cues, and templates to support the cognitive regulation skills of students during a fluid dynamics task. Students were asked to produce two learning outcomes of their investigations: system dynamics models and lab reports. Results from the three studies indicated trends in frequent use of the PC for planning activities, but low usage for monitoring and evaluation. Correlational analysis revealed two trends with regard to how these regulative activities impacted learning outcomes. First, consistent positive correlations were apparent between regulative activities and lab report scores of students and second, consistent negative correlations between the use of supports and model quality scores. Trends with regard to how task complexity, time, and student prior experience impacted these findings are also presented with suggestions for future research.

Supporting reflective web searching in elementary schools

In this contribution, two design experiments are presented in which reflective web searching is implemented in six elementary classrooms. Reflective web searching is viewed to comprise three steps: (1) develop ownership over search questions, (2) interpret and personalize web content, and (3) adapt web content into personally meaningful answers. A portal and a worksheet supported reflective web searching. A wide range of qualitative data, including observations, interviews and group products, was collected to gain insight in the emerging practices. The findings show that the portal and worksheet successfully contributed to the development of ownership, and the interpretation and personalization of retrieved information. Enabling children to search the web collaboratively further enhanced interpretation and personalization. The prototypes of both portal and worksheet were improved across the design experiments, and their success rates increased. Despite the improvements, the process of adaptation was not sufficiently supported by the portal and worksheet.

Finding Out How They Find It Out: An Empirical Analysis of Inquiry Learners' Need for Support.

Inquiry learning environments increasingly incorporate modelling facilities for students to articulate their research hypotheses and (acquired) domain knowledge. This study compared performance success and scientific reasoning of university students with high prior knowledge (n = 11), students from senior high‐school (n = 10), and junior high‐school (n = 10) with intermediate and low prior knowledge, respectively, in order to reveal domain novices’ need for support in such environments. Results indicated that the scientific reasoning of both groups of high‐school students was comparable to that of the experts. As high‐school students achieved significantly lower performance success scores, their expert‐like behaviour was rather ineffective; qualitative analyses substantiated this conclusion. Based on these findings, implications for supporting domain novices in inquiry learning environments are advanced.

Collaborative versus individual use of regulative software scaffolds during scientific inquiry learning

Scaffolds to plan, monitor, and evaluate learning within technology-enhanced inquiry and modeling environments are often little used by students. One reason may be that students frequently work collaboratively in these settings and their group work may interfere with the use of regulative supports. This research compared the use of regulative scaffolds within an inquiry and modeling environment by paired and single students. Pairs were predicted to make less use of regulative scaffolds than singles. To validate this assumption 42 high-school students worked either individually (n = 18) or in pairs (n = 12) within an inquiry learning environment. Two regulative scaffolds were used by both conditions to assist them with planning, monitoring, and evaluating their investigative efforts; a cognitive tool called the Process coordinator and a Laboratory report template. Results showed that pairs achieved significantly higher learning outcomes than individual students, and although there was a strong trend of increased regulative tool use by individual students, the frequency and duration of regulative tool use did not differ significantly between conditions. Implications of these effects for regulative scaffold design and use are discussed and suggestions for future research are advanced.

The Guided Discovery Learning Principle in Multimedia Learning

The signaling principle, also known as the cueing principle, refers to the finding that people learn more deeply from a multimedia message when cues are added that guide attention to the relevant elements of the material or highlight the organization of the essential material. This chapter reviews the main findings from research on signaling in multimedia learning addressing the effects of incorporating cues into the text, the picture, or both. Text-based cues can consist of sentences that precede the learning materials and highlight their organization. Picture-based cues can consist, for instance, of arrows in which case they are extrinsic in the sense that an element is added to the picture. The chapter considers the design of cues based on eye movements and the effects of using eye movements as cues. The signaling principle may have some relation to other principles identified by the cognitive theory of multimedia learning as well.

Simulation-Based Inquiry Learning and Computer Modeling

Background. Inquiry learning environments increasingly incorporate simulation and modeling facilities. Students acquire knowledge through systematic experimentation with the simulations and express that knowledge in runnable computer models. Aim. As inquiry and modeling activities are new and demanding for students, support for learning is needed. This article reports three experimental studies that examine how students’ inquiry and modeling activities can be supported. Need for support. Study 1 was an empirical assessment of students’ support needs. It compared a group of domain novices to two more knowledgeable reference groups in order to determine the novices’ support needs. Model progression and worked examples. In Studies 2 and 3, the need for support was addressed by model progression (gradually increasing task complexity) and worked-out examples, examining the effect of those interventions on students’ performance and learning. Results suggest positive effects due to both increasing model complexity and providing worked examples that show what the activities in each model progression phase entail and how they should be performed. Implications. The pattern of results across the three studies are discussed with regard to students’ use of available resources, influence of prior knowledge, and the relationship between performance and learning.

Modelling human emotions for tactical decision-making games

The training of tactical decision making increasingly occurs through serious computer games. A challenging aspect of designing such games is the modelling of human emotions. Two studies were performed to investigate the relation between fidelity and human emotion recognition in virtual human characters. Study 1 compared five versions of a virtual character that expressed emotions through different combinations of posture, facial expression, and tone of voice. Results showed that emotion recognition was best when all three behavioural cues were present; posture + face and posture + tone of voice were joint second best. In study 2, these three versions were supplemented with contextual information. Cross-variant comparisons yielded marginal differences in emotion recognition and no differences in tactical decision making. Together, these findings suggest that the combination of posture with either facial expression or tone of voice is sufficient to ensure recognition of human emotions in tactical decision-making games