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Computer-supported inquiry learning has the potential to foster productive engagement with the task and also enhance students' motivation. This may occur because students have the opportunity to collaborate around on authentic problems, often situated in media-rich environments. However, we have limited understanding of the quality of engagement fostered in these contexts and how technology might support high quality engagement. This study explores technological affordances on influencing students' engagement technology-rich curriculum unit on aquatic ecosystems.
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The Role of Technologies in Facilitating Collaborative Engagement
Suparna Sinha, Karlyn Adams, Toni Kempler Rogat, Cindy E. Hmelo-Silver
Rutgers University, 10 Seminary Place, New Brunswick, NJ,,,
Abstract: Computer-supported inquiry learning has the potential to foster productive
engagement with the task and also enhance students' motivation. This may occur because
students have the opportunity to collaborate around on authentic problems, often situated in
media-rich environments. However, we have limited understanding of the quality of
engagement fostered in these contexts and how technology might support high quality
engagement. This study explores technological affordances on influencing students’
engagement technology-rich curriculum unit on aquatic ecosystems.
Previous research has identified design features of technologies that foster self-regulation and high quality
engagement (Azevedo, 2005; Gresalfi, et al., 2009). Current research suggests that students can be engaged if
given opportunities to work in computer-supported, inquiry based learning environments (rvela & Salovaara,
2004; Veermans & rvela, 2004). However, we have limited understanding of the specific affordances for
students’ engagement in these technology-enhanced settings, as well as the range in quality of engagement
fostered in these contexts. Our primary research interest here is to compare the extent to which computer
technologies with varying features promote two forms of engagement- task and conceptual-to-consequential
(Gresalfi, et al., 2009), in middle school science students. Facilitating high quality engagement is critical given
benefits of engagement for learning outcomes.
Defining engagement
We define high quality task engagement (TE) as attempts to plan, monitor the plan’s enactment, and move
beyond focusing on superficial features. Planning is more than superficial when it moves toward the task
solution and problem solving. Conceptual-to-consequential (CC) engagement characterizes attempts at content
connections on a continuum that range from simple knowledge telling (low), to content connections (moderate),
to connections to prior knowledge, everyday experiences or the larger problem (i.e., consequential engagement).
Instructional context
Over the course of a 6-week 7th grade science unit, two four-student groups were videotaped as they
investigated possible causes of fish death in a pond. Students used Net Logo simulations (Wilensky & Reisman,
2006) to explore aquatic ecosystem processes (see Figure 1) to uncover the cause of lack of oxygen for the fish,
and the Ecological Modeling Toolkit (EMT; Vattam et al, 2011) to model their evolving understanding of the
problem (see Figure 2). We predicted that the simulations would foster moderate CC engagement because we
anticipated students would engage in interpret the simulations without making connections to the larger
problem. In comparison, we predicted EMT would foster high quality CC engagement given the opportunities to
make sense of data gathered from multiple sources that they would then integrate into their evolving
explanatory models. Two full-lesson observations per group were selected for analysis; as students worked with
simulations and then as they revised their models using EMT. Videos were segmented at five-minute intervals
and coded as high, medium or low engagement based on our definitions of TE and CC engagement; codes were
accompanied with justification.
Figure 1. Aquatic ecosystem simulation
Volume 2: Posters
Figure 2. EMT model
In contrast to our predictions, groups demonstrated higher quality TE and CC engagement using the simulations.
For example, high levels of CC engagement were observed when students set up parameters (i.e., high sunlight,
low nutrients) to recreate the problem scenario for understanding fish death. Students discussed relationships
among components (content connections) and considered how these factors may have led to the conditions that
caused fish death (CC engagement). Equally surprising, groups focused on specific, but individual, aspects of
the larger problem when working with the EMT software. This included defining the components they
considered in their model (e.g. algae, sunlight). However, groups did not go beyond to make connections among
these concepts (Figure 2). For instance, both groups discussed that high temperature is responsible for the algal
bloom, but neither connected it to lack of oxygen. Moreover, observed TE was moderate in quality, given that
planning during model creation focused on the physical layout, rather than on solving the larger problem.
There is a general concern that schools do not give students opportunities to engage with curricular content in
conceptually and consequentially meaningful ways (Gresalfi et al., 2009). If students have not been prepared to
think about conceptual connections between varying contexts, it is not likely that they will transfer what they
have learned beyond the school setting. This study is a step towards developing models of how high quality
collaborative engagement is mediated by specific technological affordances and how that affects learning and
transfer. Future work needs to generalize these findings beyond this case study and examine the relation
between conceptual and consequential engagement on one hand, and learning and transfer on the other hand.
Azevedo, R. (2005). Using hypermedia as a metacognitive tool for enhancing student learning? The role of self-
regulated learning. Educational Psychologist, 4, 199- 209.
Blumenfeld, P. C., Kempler, T. M., & Krajcik, J. S. (2006). Motivation and Cognitive Engagement in Learning
Environments. In K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 475-488).
New York: Cambridge University Press.
Gresalfi, M., Barab, S., Siyahhan, S., & Christensen, T. (2009). Virtual worlds, conceptual understanding, and
me: designing for consequential engagement. On the Horizon, 17, 21-34.
rvela, S., & Volet, S. (2004). Motivation in real-life, dynamic and interactive learning environments:
Stretching constructs and methodologies. European Psychologist, 9, 193-197.
Vattam, S., Goel, A., Rugaber, S., Hmelo-Silver, C., Jordan, R., Gray, S., et al. (2011). Understanding complex
natural systems by articulating structure-behavior-function models. Educational Technology & Society,
14, 66-81.
Veermans, M. & Järvelä, S. (2004) Generalized achievement goals and situational coping in inquiry learning.
Instructional Science, 32, 269291.
Wilensky, U. & Reisman, K. (2006). Thinking like a wolf, a sheep or firefly: Learning biology through
constructing and testing computational theories an embodied modeling approach. Cognition and
Instruction, 24, 171-209.
Volume 2: Posters
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In this chapter we briefly review the literature on motivation and cognitive engagement, and discuss how the key features of learning sciences-based environments are likely to influence them. We indicate some challenges posed by each of these features, for students and for teachers, which may have negative effects on motivation. We describe strategies for meeting these challenges, and argue that the challenges should be taken into account when designing learning environments and when enacting them in the classroom. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Purpose This paper aims to advance the idea of consequential engagement, positioning it as a necessary complement to the more common practices of supporting procedural or conceptual engagement. More than a theoretical argument, this notion is grounded in examples from the authors' work in enlisting game‐based methodologies and technologies for supporting such engagement. Design/methodology/approach Through the presentation of two example designs, an elementary statistics curriculum and an undergraduate educational psychology course, the paper attends to the potential of narratively‐rich, multi‐user virtual environments for positioning students to critically engage academic content. In particular, it discusses the importance of designing spaces that afford opportunities to understand and apply disciplinary concepts in making sense of, and potentially transforming, conceptually‐revealing scenarios. Findings The paper discusses the role of consequential engagement in supporting meaningful procedural and conceptual engagement, and the potential of these designed spaces for positioning learners to develop an appreciation both of the power of the conceptual tools they engage, and of themselves and their peers as people who use these tools. Originality/value This paper proposes a framework for design that can be applied to both real and virtual learning environments.
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Artificial intelligence research on creative design has led to Structure-Behavior-Function (SBF) models that emphasize functions as abstractions for organizing understanding of physical systems. Empirical studies on understanding complex systems suggest that novice understanding is shallow, typically focusing on their visible structures and showing minimal understanding of their functions and invisible causal behaviors. In this paper, we describe an interactive learning environment called ACT (for Aquarium Construction Toolkit) in which middle-school students construct SBF models of complex systems as a vehicle for gaining a deeper understanding of how such systems work. We report on the use of ACT in middle-school science classrooms for stimulating, scaffolding, and supporting SBF thinking about aquarium systems as examples of complex systems. We present preliminary data indicating that SBF thinking, facilitated in part by the ACT tool, leads to enhanced understanding of the behaviors and functions of aquaria. © International Forum of Educational Technology & Society (IFETS).
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Research shows that learners of all ages have difficulties deploying key cognitive and metacognitive self-regulatory skills during learning about complex and challenging topics when using open-ended learning environments such as hypermedia. This article provides an overview of the research my students and I have conducted on how the use of self-regulated learning can foster and enhance students' learning about complex science topics using hypermedia. In this article, the term metacognitive tool is used deliberately to highlight(a) the role of metacognitive and self-regulatory processes used by learners during learning and (b) the role of computer environments in prompting, supporting, and modeling students' self-regulatory processes during learning in specific learning contexts (see Azevedo, 2005). I provide an overview of research regarding the use of hypermedia to learn about complex science topics and learning more generally, illustrate how self-regulated learning can be used as a guiding theoretical framework to examine learning with hypermedia, and provide a synthesis of the laboratory and classroom research conducted by our group. Last, I propose several methods for using our findings to facilitate students' self-regulated learning of complex and challenging science topics.
Recent research on motivation has taken a leading role in the study of learning and instruction. Theory-based studies carried out in real-life, dynamic, and interactive learning environments have attempted to bridge the gap between basic and applied psychological and educational research. Constructs and methodologies have been stretched to include new, innovative features, with motivation commonly conceptualized as a dual psychological and social phenomenon and researched using multiple methodological approaches in combination. This paper discusses the major challenges faced by researchers who are grappling with those issues. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Biological phenomena can be investigated at multiple levels, from the molecular to the cellular to the organismic to the ecological. In typical biology instruction, these levels have been segregated. Yet, it is by examining the connections between such levels that many phenomena in biology, and complex systems in general, are best explained. We describe a computation-based approach that enables students to investigate the connections between different biological levels. Using agent-based, embodied modeling tools, students model the microrules underlying a biological phenomenon and observe the resultant aggregate dynamics. We describe 2 cases in which this approach was used. In both cases, students framed hypotheses, constructed multiagent models that incorporate these hypotheses, and tested these by running their models and observing the outcomes. Contrasting these cases against traditionally used, classical equation-based approaches, we argue that the embodied modeling approach connects more directly to students' experience, enables extended investigations as well as deeper understanding, and enables "advanced" topics to be productively introduced into the high school curriculum.
This study examined situation-specific coping strategies of students with different achievement goals as they take part in inquiry learning. A case study was conducted in a Finnish elementary school. 21 ten-year-old students participated in the study. Two types of data were collected: (1) Students self-reported questionnaires on achievement goals, (2) Video data on the students' learning processes and social interaction. The results revealed the importance of a situative perspective in instructional design, since the students not only differed in their coping attempts regarding their initial goals but also according to their individual situational interpretations that mediated their active coping attempts. Some of the non-learning-focused students had difficulties engaging in the working procedures. A lack of teacher's concrete and precise guidance in both cognitive and motivational sense appeared to explain this phenomenon.