Connected Learning Summit 2019

Who Played the Game Correctly? Data Signatures of Interaction in Playful Assessment                 Anthony J. Pellicone, Nathan R Holbert, Betsy DiSalvo, Matthew Berland, Vishesh Kumar, Yilang Zhao

In this paper we examine a formative playful assessment called Beats Empire, where learners use data analysis skills to take on the role of a music studio manager. We look at log data of players from classroom implementation of the game, finding three signatures: low activity, high activity with low data usage, and data-informed gameplay. Drawing from field notes and play-aloud interviews, we contextualize these data signatures in player conceptions of the game. We find that our data-informed player employed a number of contexts in interacting with the game, such as domain knowledge, game strategies, and perceptions of popular music. Furthermore, we find that money earned within the game, and achieving a win state (while both intuitively good metrics for assessment) are not as informative as gameplay signatures. We conclude by emphasizing that all three approaches to play are valid, and that each represents its own design challenge in terms of tuning the gameplay as well as creating supporting material to help players provide formative assessment to various types of players.

Election Lab: A Computer-Boardgame Hybrid Where STEM Meets Civics                                             Stuart Criley, Jasminka Criley
Election Lab combines math and civics in a game-based learning platform for middle- and high-school students. It opens the eyes of learners to the hidden but strategic role of STEM professionals in increasingly data-driven presidential campaigns. The games present learners with one of several actual election scenarios from recent history--from landslides to very tight races. The game design is a hybrid of a board game and computer, leveraging advantages of both formats.
The physical board game:
(1) uses large, high-resolution electoral maps and manipulatives;
(2) provides a hands-on experience;
(3) uses an intuitive and accessible format for planning and executing campaigns;
(4) increases accessibility for English language learners and others who may not benefit from traditional presentations of math concepts.
The accompanying computer:
(1) speeds up play with an interactive display that updates after each state battle;
(2) automatically calculates the Electoral Vote totals for each candidate;
(3) and most importantly, captures gameplay data for later statistical analysis and discussion.
The result is a novel informal learning program that uses math to understand strategies used in elections, and uses data generated from gameplay to allow learners to think like statisticians. Elections come alive when they are played, driving history learning. Finally, experiencing an election from the point of view of a campaign strategist and understanding the convoluted mechanics of the Electoral College first-hand will engage future voters, especially for populations that have historically low voter participation.

Rationale for Game-Based Learning in Engineering Education: The Case for Self-Determination Theory
Casper Harteveld, Victoria Bennett, Tarek Abdoun
In recent decades game-based learning has been explored to change education. While individual successes have been noted and various large-scale efforts initiated, structural changes remain difficult. In this paper, we argue that such systemic change can be pursued through using Self-Determination Theory (SDT) from a student and instructor perspective. We make this case in the context of engineering education and illustrate our arguments based on our experiences of implementing a civil engineering game called GeoExplorer across several institutes of higher education. The insights from this paper serve to think about how we can bring systemic changes through game-based learning in engineering education.