Quantitizing Affective Data as Project Evaluation on the Use of a Mathematics Mobile Game and Intelligent Tutoring System

Abstract

Technology�enhanced learning generally focuses on the cognitive rather than the af� echnology�enhanced learning generally focuses on the cognitive rather than the af� fective domain of learning. This multi�method evaluation of the INBECOM project (Integrating Behaviourism and Constructivism in Mathematics) was conducted from the point of view of af� fective learning levels of Krathwohl et al. (1964). The research questions of the study were: (i) to explore the affective learning experiences of the three groups of participants (researchers, teachers and students) during the use of a mobile game UFractions and an intelligent tutoring system Ac-tiveMath to enhance the learning of fractions in mathematics; and (ii) to determine the significance of the relationships among the affective learning experiences of the three groups of participants (researchers, teachers and students) in the INBECOM project. This research followed a sequential, equal status, multi�mode research design and methodol� ogy where the qualitative data were derived from the interviews with researchers, teachers and students, as well as from learning diaries, feelings blogs, and observations (311 documents) across three contexts (South Africa, Finland, and Mozambique). The qualitative data was quantitized (Saldaña, 2009), i.e. analysed deductively in an objective and quantifiable way as instances on an Excel™ spreadsheet for statistical analyses. All the data was explored from the affective per� spective by labelling the feelings participants experienced according to the affective levels of the Krathwohl et al. (1964) framework. The researchers concluded that: (i) the research participants not only received information, but actively participated in the learning process; responded to what they learned; associated value to their acquired knowledge; organised their values; elaborated on their learning; built abstract knowledge; and adopted a belief system and a personal worldview; and (ii) affirmation of affective learning at all five levels was recognised among the three groups of participants. The study raised a number of issues which could be addressed in future, like how affective levels of learning are in� tertwined with cognitive levels of learning while learning mathematics in a technology�enhanced learning environment; and how pedagogical models which take into account both cognitive and affective aspects of learning support deep learning.

Affective domain studies of K-12 computing education: a systematic review from a perspective on affective objectives

“…The following are studies of affective factors from a viewpoint of affective objectives. Nygren et al (2019) explored the experiences with mobile games and ITS for math education in terms of the affective domain of Krathwohl et al (1964). Noorhidawati et al (2015) analyzed qualitatively children's learning experience with mobile games in the cognitive, affective, and psychomotor domains.…”

“…These studies investigated participants' responses to certain educational ICTs (conditions). The ICTs were games (Boltz, 2017;Conati & Gutica, 2016;Nygren et al, 2019) and mobile apps (Noorhidawati et al, 2015).…”

“…They paid attention to the interaction between students and education environments. Nygren et al (2019) provided information on a wider range of 1 3 J. Comput. Educ.…”

“…The second reason came from reflecting educational goals (for example, perception shift and value formation) on the theme of educational games (Boltz, 2017;Ruggiero, 2015). Nygren et al (2019) has conducted research on both Type 1 and Type 2. It looked into the affective learning experiences of researchers, teachers, and students for a mathematics learning project with mobile games and ITS, based on Krathwohl's affective objectives taxonomy.…”

Computational Thinking in Context Across Curriculum: Students’ and Teachers’ Perspectives

“…With respect to the attitude of students, for example, studies explore (increased) interest in and perception of STEM and CS [8,17] and interest to pursue a CS degree [16]. Further examples focus on affective aspects such as enjoyment in the activity [12], learning experience [22], motivation [19], ownership [21], and difficulties [1].…”