Formative assessment in artificial integrated instruction: delving into the effects on reading comprehension progress, online academic enjoyment, personal best goals, and academic mindfulness

This paper investigates the effects of formative assessment (FA) via artificial intelligence (AI) on EFL students’ reading comprehension development, online academic enjoyment, personal best goals (PBGs), and academic mindfulness. To achieve this, 80 Kuwaiti students were selected through convenience sampling and divided into the experimental group (EG) and the control group (CG). Pretests were conducted to assess the initial levels of the dependent variables. The EG received AI-based instruction through the Nearpod platform, while the CG received traditional face-to-face instruction. Both groups were taught ten reading passages, and post-tests were administered to measure reading comprehension progress, online academic enjoyment, PBGs, and academic mindfulness. ANCOVA test results revealed significant differences between the post-tests of the EG and CG, with the EG showing superior performance across all measures. These findings suggest that AI-based formative assessments can substantially enhance students’ academic and psychological outcomes, providing valuable insights for EFL instructors and material designers. Future research should explore the long-term effects of AI-based learning tools in diverse educational settings.

Authors

Publication Details

Journal
Language Testing in Asia
Published
2024-10-18
DOI
https://doi.org/10.1186/s40468-024-00319-8
Citations
17
Primary Topic
Innovative Teaching and Learning Methods
Type
article
Field-Weighted Citation Impact
13.44
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Formative assessment in artificial integrated instruction: delving into the effects on reading comprehension progress, online academic enjoyment, personal best goals, and academic mindfulness

Asmaa Falah Theiyab Alazemi
17 citations
Language Testing in Asia
Innovative Teaching and Learning Methods
13.44
article

Formative assessment in artificial integrated instruction: delving into the effects on reading comprehension progress, online academic enjoyment, personal best goals, and academic mindfulness

Asmaa Falah Theiyab Alazemi
article en
17 citations

Abstract

This paper investigates the effects of formative assessment (FA) via artificial intelligence (AI) on EFL students’ reading comprehension development, online academic enjoyment, personal best goals (PBGs), and academic mindfulness. To achieve this, 80 Kuwaiti students were selected through convenience sampling and divided into the experimental group (EG) and the control group (CG). Pretests were conducted to assess the initial levels of the dependent variables. The EG received AI-based instruction through the Nearpod platform, while the CG received traditional face-to-face instruction. Both groups were taught ten reading passages, and post-tests were administered to measure reading comprehension progress, online academic enjoyment, PBGs, and academic mindfulness. ANCOVA test results revealed significant differences between the post-tests of the EG and CG, with the EG showing superior performance across all measures. These findings suggest that AI-based formative assessments can substantially enhance students’ academic and psychological outcomes, providing valuable insights for EFL instructors and material designers. Future research should explore the long-term effects of AI-based learning tools in diverse educational settings.

Language Testing in AsiaVol. 14(1)
Quality Education
Openalex Percentile: Top 1%
Innovative Teaching and Learning Methods
13.44
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.