When Easy Becomes Boring and Difficult Becomes Frustrating: Disentangling the Effects of Item Difficulty Level and Person Proficiency on Learning and Motivation

Mariola Moeyaert,Piet Desmet,Wim Van Den Noortgate,Kelly Wauters

doi:10.3390/systems4010014

Abstract

The research on electronic learning environments has evolved towards creating adaptive learning environments. In this study, the focus is on adaptive curriculum sequencing, in particular, the efficacy of an adaptive curriculum sequencing algorithm based on matching the item difficulty level to the learner’s proficiency level. We therefore explored the effect of the relative difficulty level on learning outcome and motivation. Results indicate that, for learning environments consisting of questions focusing on just one dimension and with knowledge of correct response, it does not matter whether we present easy, moderate or difficult items or whether we present the items with a random mix of difficulty levels, regarding both learning and motivation.

Highlights

The appearance and functionality of electronic learning environments have changed tremendously as a result of both technological advances and the increased attention of researchers and companies [1,2].Research is today mainly focused on creating an adaptive learning environment in which one or more characteristics of the learning environment are adapted to one or more features of the learner
Even though [12] states that such a simple curriculum can only be offered by random question sequencing, the aim of this study is to explore whether this statement can be underpinned by empirical research or whether a specific sequencing algorithm can be applied to item-based adaptive learning environments in order to improve learning efficiency, taking motivation into account
Based on the responses of the 215 study participants who filled out the questionnaire, we found that these scales are internally consistent: intrinsic motivation, consisting of four items (α = 0.732), asking students why they are engaging in the learning task; task value, consisting of six items (α = 0.836), asking students how interesting, important, and useful they find the task; and self-efficacy and performance, consisting of eight items (α = 0.937), asking students for their expectancy for success and self-efficacy

Summary

Introduction

Research is today mainly focused on creating an adaptive learning environment in which one or more characteristics of the learning environment (e.g., difficulty of the items and type of feedback) are adapted to one or more features of the learner. The learner’s feature of interest is the learner’s proficiency, and the learning environment characteristic of interest is the item difficulty level. Such a personalized/individualized learning environment can, for instance, incorporate an adaptive item curriculum sequencing algorithm that provides a sequence of items that is contingent on the performance of the learner on previous items and on the difficulty of the remaining unsolved items [6,7]

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