Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor

ABSTRACT

In this paper, we propose a new hint delivery mechanism called “Assertions” for providing unsolicited hints in a data-driven intelligent tutor. Assertions are partially-worked example steps designed to appear within a student workspace, and in the same format as student-derived steps, to show students a possible subgoal leading to the solution. We hypothesized that Assertions can help address the well-known hint avoidance problem. We also present a clustering analysis that shows patterns of productive persistence among students with low prior knowledge when the tutor provides unsolicited help in the form of Assertions. Overall, this work provides encouraging evidence that hint presentation can significantly impact how students use them and using Assertions can be an effective way to address help avoidance.

INTRODUCTION

Students often ignore these unsolicited hints [22,55]. In this work, we designed a new interface for unsolicited hints, called Assertions to address this issue, and compared its impact on student learning outcomes with that of Messages, text-based unsolicited hints that appear after student inactivity. The ultimate goal of our research is to combine the new Assertions interface with a data-driven method to determine when providing an unsolicited hint would be most beneficial and least disruptive for students.
Students could more quickly interpret Assertions based on the expectation set by formatting them like other problem-solving steps.
These features help Assertions act as partially-worked example steps, , so they maygarner the same benefits of worked examples, that have been shown to improve learning efficiency

LITERATURE REVIEW

*Aleven, V., Koedinger, K.R.: Limitations of student control: Do students know when
they need help? In: International Conference on Intelligent Tutoring Systems, pp. 292–

  1. Springer (2000)*

Aleven, V., Mclaren, B., Roll, I., Koedinger, K.: Toward meta-cognitive tutoring: A
model of help seeking with a cognitive tutor. International Journal of Artificial Intelligence in Education 16(2), 101–128 (2006)

Aleven, V., Ogan, A., Popescu, O., Torrey, C., Koedinger, K.: Evaluating the effectiveness of a tutorial dialogue system for self-explanation. In: International conference on
intelligent tutoring systems, pp. 443–454. Springer (2004)

METHOD

Participants

Conditions

Procedure

Hint Usage

Performance Measures

Prior Proficiency

Effort and Persistence

DATA ANALYSIS

Research by Summerfield explains that the speed of visual
interpretation is optimized by leveraging past experiences to form expectations. Based on this principle, we design Assertions to leverage student expectations through an isomorphic visual format that may work together with reduced text to decrease cognitive load.
user experiences can be enhanced by
using persuasion. Cialdini has created six principles of influence, including reciprocity, commitment and consistency, liking, social proof, authority, and scarcity, that can be used to influence people’s behaviors

RESULT AND FINDING

Interestingly, the majority of the AssertionsLow group students are in the Productive - High Effort- High HJR cluster, and the majority of the Messages-Low group students are in the Unproductive - Low Effort- Low HJR cluster. Most of the students in the Assertions-High and the
Messages-High groups are in the Productive - Low Effort- High HJR cluster. Since we are interested in the Low Prior Proficiency group, we performed a chisquare test to compare the distribution of the Assertions-Low and Messages Low students in the three clusters and found a significant difference (χ2 (1, N =41) = 24.73, p < 0.001). The majority of the Assertions-Low students show persistent effort as they are in the Productive - High Effort- High HJR cluster with the highest effort and unsolicited hint usage in training with productive posttest results, and this confirms our H3 hypothesis.

CONCLUSION

In this study, we investigated the impact of Assertions, a new genre of unsolicited hints, on the hint usage and posttest performance within a data-driven tutoring system. This work is novel in that it leveraged interface alone to address the help avoidance problem

DISSCUSSION

: Assertions increase the unsolicited hint usage for all students irrespective of their prior knowledge

: Assertions will lead to students with low prior knowledge to form shorter proofs faster in the posttest

: Assertions foster productive persistence among students with low prior knowledge

Assertions - a new genre of hints

There are three main limitations to this study. Assertions were provided significantly more frequently than Messages. Assertions did not seem to have a negative impact on learning, but rather leveled the playing field for students with low prior proficiency.

This study was a necessary first step to identify a hint interface that could solve the help avoidance problem. Future work could study the generalizability of this transformative new genre of unsolicited hints that use the design principles of contiguity, attention, and expectation to increase hint immediacy and persuasion to reduce help avoidance in other tutors.