Complexity and Difficulty of Items in Learning Systems

J 2022

Complexity and Difficulty of Items in Learning Systems

PELÁNEK, Radek, Tomáš EFFENBERGER and Jaroslav ČECHÁK

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

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

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

Abstract

V originále

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

Citovat

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.

@article{1783839,
   author = {Pelánek, Radek and Effenberger, Tomáš and Čechák, Jaroslav},
   article_number = {1},
   doi = {http://dx.doi.org/10.1007/s40593-021-00252-4},
   keywords = {adaptive learning; student modeling; difficulty; complexity},
   language = {eng},
   issn = {1560-4292},
   journal = {International Journal of Artificial Intelligence in Education},
   title = {Complexity and Difficulty of Items in Learning Systems},
   url = {https://doi.org/10.1007/s40593-021-00252-4},
   volume = {32},
   year = {2022}
}

TY  - JOUR
ID  - 1783839
AU  - Pelánek, Radek - Effenberger, Tomáš - Čechák, Jaroslav
PY  - 2022
TI  - Complexity and Difficulty of Items in Learning Systems
JF  - International Journal of Artificial Intelligence in Education
VL  - 32
IS  - 1
SP  - 196-232
EP  - 196-232
SN  - 15604292
KW  - adaptive learning
KW  - student modeling
KW  - difficulty
KW  - complexity
UR  - https://doi.org/10.1007/s40593-021-00252-4
N2  - 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.
ER  -

PELÁNEK, Radek, Tomáš EFFENBERGER and Jaroslav ČECHÁK. Complexity and Difficulty of Items in Learning Systems. \textit{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.

Detailed Information on Publication Record