Assessing the Learning Outcomes of Robot-Assisted Second Language Learning

Assessing the Learning Outcomes of Robot-Assisted Second Language Learning

Vasfiye Geçkin
Copyright: © 2023 |Pages: 18
DOI: 10.4018/978-1-6684-5660-6.ch005
OnDemand:
(Individual Chapters)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

Robot-assisted language learning (RALL) explores the role of educational humanoid robots in the learning of first and second language(s). Today, there is no definitive answer as to its effectiveness in the long run. Some studies report that adult L2 learners benefit from RALL in learning words while children enjoy only small gains from vocabulary instruction. The kind of feedback humanoid robots can provide in an ongoing conversation merely goes beyond facial expressions or words of encouragement. The need to upgrade the skills of educational robots and concerns with data privacy and abusive behavior towards robots are some challenges faced in RALL today. Plus, not a single study examined the role of RALL in assessing the reading abilities and pragmatic knowledge of L2 learners. This chapter focuses on the effectiveness of RALL in assessing word learning, pragmatics, grammar, listening, speaking, and reading skills in an L2 and discusses its reflection for future classroom applications.
Chapter Preview
Top

Word Learning

The crucial components of mastering a new word include learning the receptive and productive aspects of the word (Webb, 2005). Adding a new word to the vocabulary core involves transferring it from short- term to long-term memory, using it as means to negotiate meaning (Cowan, 2005; Gass, 1997) and to receive feedback (Long, 1996). Repetition and recycling the word through various channels (Cameron, 2001; Thornburry, 2002), especially when the learner has a lower affective filter with a manageable level of anxiety (Krashen, 1982), contribute to the word learning process.

Key Terms in this Chapter

Pragmatics: A subfield of linguistics which deals with understanding language use and meaning in context.

Humanoid Social Robots (HSRs): HSRs are human-made technologies that resemble people digitally or physically and are designed to interact with people.

Robot-Assisted Language Learning (RALL): The use of robots to support language learning.

Automated Speech Recognition (ASR): ASR is the technology that allows humans to use their voices to speak with a computer interface.

Complete Chapter List

Search this Book:
Reset