Complexity and Difficulty of Items in Learning Systems
| Authors | |
|---|---|
| Year of publication | 2022 |
| Type | Article in Periodical |
| Magazine / Source | International Journal of Artificial Intelligence in Education |
| MU Faculty or unit | |
| Citation | |
| web | https://doi.org/10.1007/s40593-021-00252-4 |
| Doi | http://dx.doi.org/10.1007/s40593-021-00252-4 |
| Keywords | adaptive learning; student modeling; difficulty; complexity |
| Description | Complexity and difficulty are two closely related but distinct concepts. These concepts are important in the development of intelligent learning systems, e.g., for sequencing items, student modeling, or content management. We show how to use complexity and difficulty measures in the development of learning systems and provide guidance on how to think, reason, and communicate about these notions. To do so, we propose a pragmatic distinction between difficulty and complexity measures. At the same time, we acknowledge the limitations of any simple distinction and discuss several potentially confounding issues: context, biases, and scaffoldings. We also provide an overview of specific measures and their applications in several educational domains and a detailed analysis of measures for problems in introductory programming. |
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