Björn Sjödén

Design for Off-task Interaction - Rethinking Pedagogy in Technology Enhanced Learning

In this paper, we argue for the design of off-task interaction in technology enhanced learning. This implies a rethinking of pedagogy which can substantially contribute to achieving specific learning goals. We describe a work-inprogress and provide concrete examples of how we deal with relevant issues raised by allowing for off-task interactions in an educational math game as an integrated learning system.

Transferring teaching to testing: an unexplored aspect of teachable agents

The present study examined whether socio-motivational effects from working with a Teachable Agent (TA) might transfer from the formative learning phase to a summative test situation. Forty-nine students (9-10 years old) performed a digital pretest of math skills, then played a TA-based educational math game in school over a period of eight weeks. Thereafter, the students were divided into two groups, matched according to their pretest scores, and randomly assigned one of two posttest conditions: either with the TA present, or without the TA. Results showed that low-performers on the pretest improved significantly more on the posttest than did high-performers, but only when tested with the TA. We reason that low-performers might be more susceptible to a supportive social context - as provided by their TA - for performing well in a test situation.

From Learning Companions to Testing Companions

In three quasi-experimental studies, we investigated the effects of placing a Teachable Agent (TA) from a math game in a digital summative test. We hypothesized that the TA would affect test performance, even without actual “teachability”, by social influence on the test situation. In Study 1 (N=47), students did a pretest, played the math game for seven weeks, and did a posttest either with or without the TA. In Study 2 (N=62), students did not play the game but were introduced to a TA directly in the posttest. In Study 3 (N=165), the game included a social chat with the TA, and the posttest offered a choice of more difficult questions. Results showed significant effects of the TA on choice and performance on conceptual math problems, though not on overall test scores. We conclude that experience with a TA can influence performance beyond interaction and informative feedback.

Extending an Educational Math Game with a Pedagogical Conversational Agent: Facing Design Challenges

We describe our work-in-progress of developing an educational game in mathematics for 12-14 year olds, by adding social and conversational abilities to an existing “teachable agent” (TA) in the game. The purpose of this extension is to affect cognitive, emotional and social constructs known to promote learning, such as self-efficacy and engagement, as well as enhancing students’ experiences of interacting with the agent over an extended period of time. Drawing from the EnALI framework, which states practical design guidelines, we discuss specific design challenges and exemplify research considerations as to developing the agent’s visual representation and conversational module. We present some initial findings from using prototype agents with students from the target group. Promising developments seem to reside in pronouncing the agent’s personality traits and expanding its knowledge database, particularly its range of conversational topics. Finally we propose some future studies and research directions.

Can a teachable agent influence how students respond to competition in an educational game

Learning in educational games is often associated with some form of competition. We investigated how students responded to winning or losing in an educational math game, with respect to playing with or without a Teachable Agent (TA). Students could choose between game modes in which the TA took a more passive or active role, or let the TA play a game entirely on its own. Based on the data logs from 3983 games played by 163 students (age 10–11), we analyzed data on students’ persistence, challenge-seeking and performance during gameplay. Results indicated that students showed greater persistence when playing together with the TA, by more often repeating a lost game with the TA, than a lost game after playing alone. Students’ challenge-seeking, by increasing the difficulty level, was greater following a win than following a loss, especially after the TA won on its own. Students’ gameplay performance was unaffected by their TA winning or losing but was, unexpectedly, slightly worse following a win by the student alone. We conclude that engaging a TA can make students respond more productively to both winning and losing, depending on the particular role the TA takes in the game. These results may inform more specific hypotheses as to the differential effects of competing and collaborating in novel, AI-supported social constellations, such as with TAs, on students’ motivation and ego-involvement in educational games.

From Learning Companions to Testing Companions Experience with a Teachable Agent Motivates Students' Performance on Summative Tests

In three quasi-experimental studies, we investigated the effects of placing a Teachable Agent (TA) from a math game in a digital summative test. We hypothesized that the TA would affect test performance, even without actual “teachability”, by social influence on the test situation. In Study 1 (N=47), students did a pretest, played the math game for seven weeks, and did a posttest either with or without the TA. In Study 2 (N=62), students did not play the game but were introduced to a TA directly in the posttest. In Study 3 (N=165), the game included a social chat with the TA, and the posttest offered a choice of more difficult questions. Results showed significant effects of the TA on choice and performance on conceptual math problems, though not on overall test scores. We conclude that experience with a TA can influence performance beyond interaction and informative feedback.