Influence of the NAO robot as a teaching assistant on university students’ vocabulary learning and attitudes
Keywords:NAO robot, RALL, computer-assisted language learning (CALL), attitudes, vocabulary learning and teaching, mixed method
This study investigated how the NAO robot as a teaching assistant affects the way university students learn vocabulary and their attitudes towards it. A mixed method approach was followed to gather both quantitative and qualitative data. A quasi-experimental design, including a pre-test and a post-test, was employed to explore the impact of the NAO robot on students’ vocabulary learning. Moreover, a questionnaire and an interview were used to identify the attitudes of the participants towards the NAO robot. The participants, who were taking a vocabulary course for language improvement as part of the regular curriculum of the program during the experiment, were freshman students of the English language teaching undergraduate program at a higher education institution in North Cyprus. Of the two groups, the control group performed slightly better than the experimental group even though the analyses did not show any statistically significant difference between them. Descriptive data analysis showed that most of the students liked the NAO robot and its abilities. However, related findings from the qualitative data were mixed. Most participants liked the NAO robot and thought that the robot helped them to learn the new words, while some thought that the technology needed to be improved.
Implications for practice or policy:
- Evidence of vocabulary gains and students’ generally positive attitudes mark the NAO robot as a promising tool in language learning and teaching.
- The benefits and drawbacks of the NAO robot should be taken into account prior to its integration into second language vocabulary learning and teaching.
- In alignment with the continuous assessment of developments in robot-assisted language learning research, teachers should be provided with professional training for using the NAO robot effectively with various learners.
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