Title: Opening the Black Box. Students' Tool-use within a Technology-Enhanced learning environment: An Ecological-Valid Approach
Authors: Lust, Griet
Issue Date: 21-Dec-2012
Abstract: Already in the 80s, Winne (1982) argued that research on learning from instruction is mostly focused on the instructional stimuli as such and its’ effects on learning assuming that all learners process the stimuli as intended. Students’ actual processing of the instructional stimuli remains, he argued, a black box that is largely undocumented within research but needs more consideration. Research that investigates students’ tool-use within technology-enhanced learning environments opens Winne’s black box and stresses its’ importance. In this respect, tools are defined as all those instructional (technology-supported or face-to-face) stimuli that are deliberately integrated into or added to the learning tasks and learning content in view of fostering students’ learning. Although these tools provide, theoretically, learning support, evidence suggests that only a minority of students profits from this learning support. Particularly, throughout multiple studies it was revealed that students’ tool-use is on average suboptimal i.e., on average tools are neglected or used in other ways as intended which had in most studies significant performance effects. In terms of Winne’s (1982) black box, current tool-use evidence implies that the learning effectiveness of a learning environment depends on students’ adaptive tool-use or using tools in line with the learning task requirements. Nevertheless, current tool-use evidence indicates that this black box problem cannot be minimized since only a minority of students used the available tools adaptively. Consequently, more research on students’ adaptive tool-use seems necessary from an instructional design perspective. Current tool-use evidence is however mainly retrieved in controlled, technology-enhanced, learning environments that were uniquely designed for the research purpose. These controlled learning environments differ inherently from realistic, technology-enhanced learning environments in terms of tool-set, learning tasks and learning episode. As a consequence, the ecological validity of current tool-use evidence can be questioned. The current dissertation addressed this ecological validity and investigated students’ tool-use throughout an ecological technology-enhanced learning environment. As an introduction (cf. chapter 1), the dissertation hypothesized on a model of adaptive tool-use and its’ main components based on an analysis of the existing tool-use research and relevant theoretical frameworks i.e., Winne’s (1982) cognitive conditions, Perkin’s (1985) framework and Nelson Le Gall’s (1985) and Newman’s (1994) help-seeking model. In this respect, tool-use is conceptualized as a self-regulated strategy wherein students can regulate (a) the tools that they select (tool-diversity), (b) the way these tools are used (tool-activeness) and (c) the moment these tools are selected within the learning episode (tool-consistency). Adaptive tool-use on the other hand was conceptualized as (a) selecting those tools that are functional for the learning task at hand (tool-diversity ), (b) use these tools as intended by the instructional designer (tool-activeness) and (c) reflect and monitor this tool-choice when learning tasks change accordingly (tool-consistency). Throughout three studies, the empirical validity of this model was investigated. The first study (cf. chapter 2) that was executed was a literature review that explored current tool-use evidence within content management supported courses i.e., the type of learning environment that was used throughout the PhD. Particularly, the literature review presented an overview over the existing research on students’ tool-use within CMS supported courses and related the main findings to our tool-use model. With respect to the latter, existing evidence was analyzed in relation to (a) students’ agency in tool-use, (b) performance effects of tool-use and (c) influencing student variables. The second study was an empirical study that aimed to explore the importance of the three components of adaptive tool-use i.e., diversity, activeness and consistency. Particularly, it was explored within chapter 3 whether student differences in tool-use reflect different tool-use patterns that mark differences in (a) students’ tool-diversity and (b) students’ tool-activeness. Additionally, it was investigated whether these differences affected students’ learning significantly and are hence important to consider. Chapter 4 explored whether students differed significantly in the moment tools were accessed (tool-consistency) and whether these temporal differences influenced students’ performance as well. The final empirical study was mainly focused on (1) replicating the tool-use patterns of the previous study with a new student group, (2) investigating the conditional factors for students’ tool-use and (3) investigating the importance of students’ tool-diversity, tool-activeness and tool-consistency in one analysis. The different findings of these two empirical studies are related to each other and to our tool-use model in the conclusion. Additionally, new research opportunities are addressed that come out of these findings.
Publication status: published
KU Leuven publication type: TH
Appears in Collections:Instructional Psychology and Technology

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