Join a discussion about co-design approaches that can help ensure that educational innovations are designed and used to support teaching and learning in early childhood.
Consider multiple approaches to valuing, supporting, and studying the diversity of students’ solutions to design problems through poster presentations and small-group discussion.
“Solution diversity” has been proposed as one key characteristic that distinguishes engineering design from other disciplinary pursuits. Engineering designers recognize that for any design problem, there will be multiple acceptable solutions, and informed designers have been found to strive for “idea fluency” through divergent thinking techniques that assist them in exploring the design space (Crismond & Adams, 2012).
Discover how digital games can inform classroom teaching using data from innovative formative assessments from three different game-based projects.
This session aims to open up a conversation about of how games can be used for formative assessment and how data from digital games can inform classroom teaching.
Join a facilitated discussion about the application of data science to education, drawing on a recent NSF-sponsored report. Participants share insights from DR K–12 projects.
The Computing Research Association’s report from an NSF-sponsored workshop describes seven next steps for data-intensive research in education:
Powell, A. B., & Alqahtani, M. M. (2015). Promoting productive mathematical discourse: Tasks in collaborative digital environments. In T. G. Bartell, K. N. Bieda, R. T. Putnam, K. Bradfield, & H. Dominguez (Eds.), Proceedings of the 37th annual meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education (pp. 1246-1249). East Lansing, MI: Michigan State University.
Tasks can be vehicles for productive mathematical discussions. How to support such discourse in collaborative digital environments is the focus of our theorization and empirical examination of task design that emerges from a larger research project. We present our task design principles that developed through an iterative research design for a project that involves secondary teachers in online courses to learn discursively dynamic geometry by collaborating on construction and problem-solving tasks in a cyber learning environment. In this study, we discuss a task and the collaborative work of a team of teachers to illustrate relationships between the task design and productive mathematical discourse. Implications suggest further investigations into interactions between characteristics of task design and learners mathematical activity.
Alqahtani, M. M., & Powell, A. B. (2015, March). Instrumental development of teachers’ reasoning in dynamic geometry. Paper presented at the 2015 annual meeting of the American Educational Research Association, Chicago, IL.
To contribute to understanding how teachers can develop geometrical understanding, we report on the discursive development of teachers’ geometrical reasoning through instrument appropriation while collaborating in an online dynamic geometry environment (DGE). Using the theory of instrument-mediated activity, we analysis the discourse and DGE actions of a group of middle and high school mathematics teachers who participated in a semester-long, professional development course. Working in small teams, they collaborated to solve geometric problems. Our results show that as teachers appropriate DGE artifacts and transform its components into instruments, they develop their geometrical knowledge and reasoning in dynamic geometry. Our study contributes to a broad understanding of how teachers develop mathematical knowledge for teaching.
Powell, A. B., & Alqahtani, M. M. (2015). Tasks promoting productive mathematical discourse in collaborative digital environments. In N. Amado & S. Carreira (Eds.), Proceedings of the 12th International Conference on Technology in Mathematics Teaching. (pp. 68-76). Faro, Portugal: Universidade do Algarve.
Rich tasks can be vehicles for productive mathematical discussions. How to support such discourse in collaborative digital environments is the focus of our theorization and empirical examination of task design that emerges from a larger research project. We present the theoretical foundations of our task design principles that developed through an iterative research design for a project that involves secondary teachers in online courses to learn discursively dynamic geometry by collaborating on construction and problem-solving tasks in a cyberlearning environment. In this study, we discuss a task and the collaborative work of a team of teachers to illustrate relationships between the task design, productive mathematical discourse, and the development of new mathematics knowledge for the teachers. Implications of this work suggest further investigations into interactions between characteristics of task design and learners mathematical activity.
Pallant, A., & Lee H.-S. (2015). Constructing scientific arguments using evidence from dynamic computational climate models. Journal of Science Education and Technology. 24 (2-3) 378-395. doi 10.1007/s10956-014-9499-3.
Modeling and argumentation are two important scientific practices students need to develop throughout school years. In this paper, we investigated how middle and high school students (N=512) construct a scientific argument based on evidence from computational models with which they simulated climate change. We designed scientific argumentation tasks with three increasingly complex dynamic climate models. Each scientific argumentation task consisted of four parts: multiple-choice claim, open ended explanation, five-point Likert scale uncertainty rating, and open-ended uncertainty rationale.
We coded 1,294 scientific arguments in terms of a claim’s consistency with current scientific consensus, whether explanations were model based or knowledge based and categorized the sources of uncertainty (personal vs. scientific). We used chi-square and ANOVA tests to identify significant patterns. Results indicate that (1) a majority of students incorporated models as evidence to support their claims, (2) most students used model output results shown on graphs to confirm their claim rather than to explain simulated molecular processes, (3) students’ dependence on model results and their uncertainty rating diminished as the dynamic climate models became more and more complex, (4) some students’ misconceptions interfered with observing and interpreting model results or simulated processes, and (5) students’ uncertainty sources reflected more frequently on their assessment of personal knowledge or abilities related to the tasks than on their critical examination of scientific evidence resulting from models. These findings have implications for teaching and research related to the integration of scientific argumentation and modeling practices to address complex Earth systems.
James Paul Gee presents a theory of STEM learning based on embodied cognition with a focus on the role of experience and language; discusses the role of digital media in powerful new forms of teaching and learning outside of school; and considers the wider framework within which STEM should sit in our world.
Jodi Asbell-Clarke, TERC | June 29, 2016
Hearing Jim Gee talk is always a treat. As one colleague said: “I always come away feeling both inspired and doomed.” Jim thinks, or at least speaks, differently than most people I know. He is willing to look our world’s problems right in their face, outline all the ugly and fear-inducing truths in our lives…and then provide a totally different way of looking at these issues.
In his session at the 2016 DR K-12 PI Meeting, Jim painted a pretty dire picture of the state of our world and the state of science education in the US. He linked these two, noting that the type of thinking needed to provide solutions for our world’s biggest problems requires scientific thinking – something that is scarily on the decline (and even objected to) in the US today. And something at which, he argued, our schools are failing to promote.
He also explained that well designed experiences for learning must engage the learners’ affect. In other words, the learner must care about the experience. They should focus on an action or problem from which the learner can build an expectation or hypothesis, there should be a feedback system that helps the learner assess the outcomes of the action in terms of their hypothesis, and they must provide some way of managing the learner’s attention.
Jim seeks well designed learning environments and has found them in many digital games. Well, not always in the games themselves, more in the affinity spaces that surround them. He argues that digital games provide many elements of good design for learning environments and also provide rich opportunity for negotiation of language to make meaning. By studying the interactions in the user groups and social media sites surrounding multi-player games like World of Warcraft (WoW), game-based learning researchers have observed knowledge building behaviors that rival formal education programs, and many times these programs are reaching kids who are disengaged with school (e.g. Steinkeuhler & Duncan, 2008).
In this session, Jim emphasized the contextual underpinnings of any learning experience, giving examples to illustrate how much language and situation can impact meaning for different individuals. He explained how when we use a complex term, such as “democracy,” we bring our own preconceptions of that term, along with our skills and biases, to how we choose to parse its meaning in a sentence. The nuance of any term or phrase may be implicit in the context of a particular situation, and teasing out that nuance is a skill that requires expertise and even still can be subjective.
For DR K-12 educators, I think the most relevant take-away from Jim’s talk is to look for learning where you least expect it. Find the environments that are engaging youth and leverage those environments to support and measure STEM learning. Don’t use the limitations of contextualization as a reason to avoid reaching learners where they are most engaged.
Our work at EdGE at TERC builds directly from this message. We use digital game environments where learners choose to dwell, and underlay those environments with rich opportunities to build implicit understanding of STEM phenomena. By keeping the games free of any formalisms or “teaching” language, we let players’ behaviors with the phenomena guide their learning. The games provide feedback realistic to the scientific problem, and the player learns by grappling with the game.
Clearly, in order for game-based learning to be productive, it should transfer to something useful in the learners’ life outside the game. Much of what happens during gameplay (be it within the game or within the affinity space) could remain implicit learning, learning that is not expressed formally by the learner. Methods are needed to recognize the skills and knowledge that is built in games as well as to build game-based learning assessments that teachers can use to help bridge to useful, “real-world” skills and knowledge. Teachers could be a key vehicle in bridging from implicit, game-based learning to explicit learning, if armed with information about what their students are learning in games.
Over a decade ago, Jim set the stage for the game-based learning assessment field by famously saying “No one gives someone who has finished Halo on the hard difficulty level a Halo test after they have won the game.” Val Shute coined the term “stealth assessment” to describe assessments of knowledge and skills that were so embedded in the activity that the learner didn’t even know they were being assessed (Shute, 2011; Shute & Ventura, 2013; Shute, Ventura, Bauer, & Zapata-Rivera, 2009). Putting these ideas together, a growing community of educational data mining researchers are building sophisticated and innovative analytics to use the vast logs of digital “clickstream” data generated by games—logs of every player action and associated game state, tagged with a timestamp and PlayerID.
Now, game-based analytics are allowing researchers to see the patterns of behaviors learners exhibit in game spaces much like Amazon or Facebook analyzes consumer behaviors. This provides a powerful formative assessment tool that shows promise for measuring learning at a more implicit level and from a broader range of learners than ever before. With tools like this, Jim’s suggestion of distributed teaching systems —where learning and interactions that take place in game can be leveraged for other learning experiences—are becoming a reality.
Shute, V. (2011). Stealth assessment in computer-based games to support learning. In S. Tobias & J.D. Fletcher (Eds.), Computer games and instruction (pp. 503-524). Charlotte, NC: Information Age Publishers.
Shute, V., & Ventura, M. (2013). Stealth assessment: Measuring and supporting learning in video games. Cambridge, MA: The MIT Press.
Shute, V., Ventura, M., Bauer, M., & Zapata-Rivera, D. (2009). Melding the power of serious games and embedded assessment to monitor and foster learning: Flow and grow. In U. Ritterfeld, M. Cody, & P. Vorderer (Eds.), Serious games: Mechanisms and effect (pp. 295-321). Mahwah, NJ: Routledge, Taylor and Francis.
Steinkuehler, C., & Duncan, S. (2008). Scientific habits of mind in virtual worlds. Journal of Science Education and Technology, 17(6), 530-543.