Computer-Assisted Language Learning (CALL)

Computer-Assisted Language Learning (CALL)

Computer-Assisted Language Learning (CALL)

In recent decades, CALL researchers have explored a range of technologies and pedagogical approaches such as interface design and authoring, data management and access, intelligent tutoring systems, speech recognition technologies, and natural language (Stockwell, 2007). 

The areas most extensively studied in CALL research over time include grammar, vocabulary, speaking, and writing. Also, CALL has been applied and studied more actively in the context of secondlanguage learning than in first-language learning. For example, in a study with 122 Korean tenth-graders who learn English as a foreign language, 

Yun and colleagues (2008) found that constructed-response (fill-in-the-blank) questions with explicit feedback in CALL were effective for improving the learners’ recall of vocabulary and transfer. Chen and Wang (2008) tested several of Ellis’s language learning principles in collaborative cyber-community-based learning, with seven 

1- Chinese EFL learners in a college and 
found that the use of text chat and joint web browsing helped foster communicative language skills in synchronous online classes. In contrast to the growing amount of CALL research, the use of CALL to teach reading has been relatively limited and has even shown a consistently decreasing trend over the last decade (Stockwell, 2007). 

Furthermore, among the existent CALL applications for reading, the majority deals with discrete skills development like vocabulary building and word recognition. A meta-analysis of CALL research in reading indicates that most research has focused on developing phonemic awareness, letter identification, word identification, and speed and fluency in reading words (Blok, Oostdam, Otter, & Overmaat, 2002). 

2- There has been a dearth of CALL research to examine the effectiveness of 
CALL for reading comprehension instruction. Reading comprehension could be better taught in social and interactive contexts, as recommended by many reading researchers. Although CALL applications afford individualized instruction conventionally, they often fall short of integrating social interaction. 

Therefore, the author explored animated, digital peer technology to see if the technology would expand the capacity of CALL by rendering a social context that might benefit young readers. Virtual peer The term virtual peer refers to an animated, digital character, a subset of a more broadly used term pedagogical agents (animated life-like characters embedded in educational applications). 

It is well acknowledged that people, consciously or unconsciously, tend to ascribe mental states to computers and interact with computers socially (Kim, 2007; (Reeves & Nass, 1996). Virtual peer technology seems to broaden the communication bandwidth between a learner and a computer. It has been used to render social presence and enrich learning experiences in computer-based learning (Gulz, 2005; Iacobelli & Cassell, 2007; Johnson, Rickel, & Lester, 2000). 

3- A number of researchers in pedagogical agents
 support consistently that the social presence produces positive gains in learner affect and engagement (Atkinson, 2002; Dempsey & van Eck, 2003; Gulz, 2004; Johnson, et al., 2000; Kim & Wei, 2011; Mayer, Johnson, Shaw, & Sandhu, 2006; Moreno & Mayer, 2000; Plant, Baylor, Doerr, & Rosenberg-Kima, 2009). 

Moreover, some studies argue for the modeling effect (Kim & Baylor, 2007; Ryokai, Vaucelle, & Cassell, 2003). Kim and Baylor (2007) claimed that the use of virtual peers as role models for learners could be viable for enhanced motivation and learning, in that a virtual peer playing as a coping or mastery model could motivate the learner toward challenging and less popular domains of learning. 

4- Embedded in computer-based reading instruction, 
A virtual peer could be designed to explicitly demonstrate reading strategy use and encourage a young reader to use the strategy. Through the peer’s modeling (Bandura, 2001; Schunk & Hanson, 1989), the learner might vicariously learn the strategy use and improve their text comprehension. 

Further, the peer’s visual and verbal demonstration is likely to lessen young readers’ burden to read through explanations in text or graphics (i.e., reducing cognitive load) and, thereby, improve the efficacy of strategy instruction. 

5-VRyokai and colleagues’ study (2003)
hinted this modeling effect. In their study, children who played with the virtual peer Sam listened to Sam’s stories carefully and mimicked Sam’s linguistic styles in their speech. It seemed that Sam played a social role for the children. 

The children might feel affiliated with Sam, which, presumably, induced their behavioral changes. A similar modeling impact was implied in an online tutoring game teaching phonemic decoding skills, where children’s skills increased only when the program included a digital tutor that gave oral feedback to the children (Kegel & Bus, 2012). 

Given the lack of computer-based reading-comprehension instruction, the author developed a reading lesson, Affable Reading Tutor (ART) to model the use of comprehension strategy for children who just started reading to comprehend. In the lesson, the children studied finding cause-and-effect relationship in expository texts, observing a virtual peer’s strategy use. 

6- The young readers might be able to develop 
Social relations and interact socially with the peer, which would be beneficial for their motivation and text comprehension. The author investigated the impact of the peer serving as a peer model that demonstrated strategy use to increase the learners’ text comprehension. 

This study was focused on how effectively a virtual peer’s modeling of reading strategy use would improve children’s text comprehension, compared to the strategy instruction without virtual-peer presence. The primary research question asked 1) Will the presence of a virtual peer influence learners’ text comprehension? 

7- Also, referring to the current literature in virtual peers 
(or pedagogical agents), two additional questions were asked. The second question was about learner gender because learner gender was often a factor determining the effectiveness of agent presence (Baylor & Kim, 2005; Kim, Baylor, & Shen, 2007). The second question asked 2) Will learner gender and virtual-peer presence interact to influence text comprehension? 

The third question was about learners’ perceptions of virtual-peer attributes. Researchers in agent technology emphasize a learner’s building social relations with their agent in order to maximize its instructional effectiveness (Dautenhahn, Bond, Canamero, & Edmonds, 2002). 

8- How a learner would perceive their virtual 
Peer seems to be a meaningful factor for the efficacy of the learning environment. At the same time, much of agent research indicates learners’ sensitive reactions to agent attributes, such as gender and appearance (Baylor & Plant, 2005; Haake & Gulz, 2008; Kim, Wei, Xu, & Ko, 2007). 

In particular, Haake and Gulz (2008) argue that an agent’s visual appearance carries social baggage that could activate a learner’s expectations of the agent. The third question asked 3) Will learner gender and virtual-peer attributes interact to influence learners’ perceptions of a virtual peer?

Participants were 141 children in the fourth and fifth grades (68 boys and 73 girls) in an elementary school located in a mountain-west state in the United States. Access to the participants was achieved by collaborating with classroom teachers who volunteered to use .

The intervention environment in their classes. The study was implemented as a mandatory class activity. The participants were randomly assigned to experimental conditions by the system programming. 

Post a Comment

Previous Post Next Post