Complexity and Difficulty of Items in Learning Systems

PELÁNEK, Radek, Tomáš EFFENBERGER and Jaroslav ČECHÁK. Complexity and Difficulty of Items in Learning Systems. International Journal of Artificial Intelligence in Education. 2022, vol. 32, No 1, p. 196-232. ISSN 1560-4292. Available from: https://dx.doi.org/10.1007/s40593-021-00252-4.

Basic information

• Original name: Complexity and Difficulty of Items in Learning Systems
• Authors: PELÁNEK, Radek (203 Czech Republic, guarantor, belonging to the institution), Tomáš EFFENBERGER (203 Czech Republic, belonging to the institution) and Jaroslav ČECHÁK (203 Czech Republic, belonging to the institution).
• Edition: International Journal of Artificial Intelligence in Education, 2022, 1560-4292.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: Switzerland
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• Impact factor: Impact factor: 4.900
• RIV identification code: RIV/00216224:14330/22:00124952
• Organization unit: Faculty of Informatics
• Doi: http://dx.doi.org/10.1007/s40593-021-00252-4
• UT WoS: 000647045400001
• Keywords in English: adaptive learning; student modeling; difficulty; complexity
• Tags: International impact, Reviewed

Abstract

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.

Links

• MUNI/A/1549/2020, interní kód MU: Name: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 21 (Acronym: SKOMU)

Investor: Masaryk University

• MUNI/A/1573/2020, interní kód MU: Name: Aplikovaný výzkum: vyhledávání, analýza a vizualizace rozsáhlých dat, zpracování přirozeného jazyka, umělá inteligence pro analýzu biomedicínských obrazů.

Investor: Masaryk University