The Design of an Adaptive Tool Supporting Formative Assessment in Data Science Courses

被引：2

作者：

Vittorini, Pierpaolo ^{[1
]}

机构：

[1] Univ Aquila, I-67100 Laquila, Italy

来源：

LEARNING TECHNOLOGIES AND SYSTEMS, ICWL 2022, SETE 2022 | 2023年 / 13869卷

关键词：

Adaptive Assessment; Automated Correction; User-Centered Design; Data Science Assignments;

D O I：

10.1007/978-3-031-33023-0_8

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The automated correction of assignments is a task that received large support from artificial intelligence. In previous research, we approached the problem of automatically providing a grade and feedback to students in solving data science exercises, that resulted in the development of the rDSA tool. In this paper, we discuss the first steps towards the development of an adaptive system - based on the rDSA tool - supporting the students' formative assessment activities. In particular, we present the context of use, the requirements - elicited through a study with a small cohort of students, the models enabling adaptation, and the user interface. Finally, we evaluated the user interface through a further study that involved both qualitative and quantitative measures.

引用

页码：86 / 97

页数：12

共 18 条

[1]

Albert B., 2013, MEASURING USER EXPER

[2]

Andersen E.B., 1997, Handbook of modern item response theory, P67, DOI [10.1007/978-1-4757-2691-64, DOI 10.1007/978-1-4757-2691-64]

[3] Lessons learned about the application of adaptive testing in several first-year university courses [J].

Angelone, Anna Maria ;

Galassi, Alessandra ;

Vittorini, Pierpaolo .

INTERNATIONAL JOURNAL OF LEARNING TECHNOLOGY, 2022, 17 (01) :3-26

[4] On the Design and Development of an Assessment System with Adaptive Capabilities [J].

Bernardi, Angelo ;

Innamorati, Carlo ;

Padovani, Cesare ;

Romanelli, Roberta ;

Saggino, Aristide ;

Tommasi, Marco ;

Vittorini, Pierpaolo .

METHODOLOGIES AND INTELLIGENT SYSTEMS FOR TECHNOLOGY ENHANCED LEARNING, 2019, 804 :190-199

[5] The silent reading supported by adaptive learning technology: Influence in the children outcomes [J].

Dina, Di Giacomo ;

Cofini, Vincenza ;

Tania, Di Mascio ;

Rosita, Cecilia Maria ;

Daniela, Fiorenzi ;

Rosella, Gennari ;

Pierpaolo, Vittorini .

COMPUTERS IN HUMAN BEHAVIOR, 2016, 55 :1125-1130

[6] Automated Feedback to Students in Data Science Assignments: Improved Implementation and Results [J].

Galassi, Alessandra ;

Vittorini, Pierpaolo .

PROCEEDINGS OF THE 14TH BIANNUAL CONFERENCE OF THE ITALIAN SIGCHI CHAPTER (CHIITALY 2021), 2021,

[7]

Kabudi T., 2021, Comput Educ Artif Intell, V2, P100017, DOI [10.1016/j.caeai.2021.100017, DOI 10.1016/J.CAEAI.2021.100017]

[8] Learning Performance in Adaptive Learning Systems: A Case Study of Web Programming Learning Recommendations [J].

Ling, Hsiao-Chi ;

Chiang, Hsiu-Sen .

FRONTIERS IN PSYCHOLOGY, 2022, 13

[9]

Luckin R., 2016, Intelligence Unleashed: An Argument for AI in Education

[10] Systematic review of adaptive learning research designs, context, strategies, and technologies from 2009 to 2018 [J].

Martin, Florence ;

Chen, Yan ;

Moore, Robert L. ;

Westine, Carl D. .

ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT, 2020, 68 (04) :1903-1929

← 1 2 →