INTRODUCTION
During the last two decades, the body of research examining computer-assisted language learning (CALL) has grown, with studies investigating a wide range of second language (L2) areas of interest, including the development of linguistic, communicative, and intercultural competence. Educators have also embraced the rise of technology, with research demonstrating the increasing incorporation of computer-mediated language learning into the classroom and curriculum (e.g., Blake, Reference Blake2011; Grgurović, Chapelle, & Shelley, Reference Grgurović, Chapelle and Shelley2013; Lai & Li, Reference Lai and Li2011; Sauro, Reference Sauro2011; Zhao, Reference Zhao2003). In addition, many of today's learners have come of age during a time when technology is integrated seamlessly into many aspects of their lives. As a result of their upbringing and experiences with technology, the preferences of these learners may be more connected to technology (Prensky, Reference Prensky2001), with increasing use of multimodal combinations of mobile phone applications, text messaging, and social and visual media for learning. Because everyday cognitive activity is likely to impact learners’ development well into adulthood (Thorne & Payne, Reference Thorne and Payne2005), the effects of this change in patterns of daily technology use on L2 learning and teaching should be considered, especially as these shifts have no doubt influenced learners’ degree of interconnectedness and multitasking, as well as how they process and interact with their learning environment (Thorne, Reference Thorne and Hawkins2013).
Although many in the field of language education have sought to integrate technology into the language learning classroom, researchers have pointed out that the developmental and sociocultural benefits of technology are limited if its application and use are not grounded in sound and empirically supported approaches to language learning and teaching. Chapelle (Reference Chapelle1997, Reference Chapelle1998, Reference Chapelle2001) first drew attention to the need for a more empirically grounded approach to CALL, when, in a series of articles, she suggested that CALL research not only needed to be more firmly grounded within second language acquisition (SLA) theory, but that there was a need for researchers to inform their studies using research methods from instructed SLA (Chapelle, Reference Chapelle1997) and to design more pedagogically effective computer-based activities (Chapelle, Reference Chapelle1998). Chapelle (Reference Chapelle1997) suggested that in order to effectively evaluate the quality of learners’ language in L2 tasks, it is necessary to function according to certain assumptions about the types of language facilitative of L2 development.
Building on the idea that CALL might be developed to reflect ideal conditions for L2 development and focusing on the potential pedagogical applications of interaction in CALL, Chapelle (Reference Chapelle1998) identified seven features of interaction that could be directly applied to instruction in a computer-mediated environment, including making key linguistic features salient; offering modified input and supporting modified interaction between the learner and the interlocutor; and providing opportunities for learners to be active participants in the task: to notice their errors, modify their output, and receive comprehensible output. These principles of instructional design were based on hypotheses regarding ideal SLA conditions (Long, Reference Long, Ritchie and Bhatia1996; Pica, Reference Pica1994) and were later expanded upon by Doughty and Long (Reference Doughty and Long2003) to include features of task-based language learning and teaching, providing CALL researchers with theoretically sound foundations on which to base hypotheses regarding L2 development in computer-mediated contexts.
By using this task-based framework to construct research-oriented and instructional designs, researchers had a structured approach through which to examine and establish the ability of computer-mediated communication (CMC) to direct learners’ attention to specific target language features and to provide learners with opportunities to negotiate for meaning, receive comprehensible input and corrective feedback, and produce modified output (Smith, Reference Smith2004). In other words, tasks and technology are ideal partners in a reciprocal relationship, providing opportunities for researchers seeking to explore how the integration of technology can enhance or facilitate the benefits of task-based language teaching (TBLT) as well as addressing how TBLT can serve as a framework in which to ground research conducted in CALL contexts (e.g., Doughty & Long, Reference Doughty and Long2003; Ortega, Reference Ortega, Mackey and Polio2009; Skehan, Reference Skehan2003). Recently, González-Lloret and Ortega (Reference González-Lloret, Ortega, González-Lloret and Ortega2014) addressed the need for a new conceptualization of technology-mediated TBLT, where tasks and task-based curricula acknowledge and embrace the integration of technology as not only a medium but also as an opportunity for learning by doing, providing opportunities for learners’ to improve their digital literacy and real-world technology skills.
Responding to these calls for a more synergistic relationship between technology and TBLT, research has demonstrated unique advantages and affordances for various types of technology in task-based environments, as well as provided evidence for the use of TBLT as a framework for implementing technology in the language learning classroom. The findings indicate that technology not only facilitates and supports the development of linguistic (e.g., Salaberry, Reference Salaberry2000; Sauro, Reference Sauro2009) and pragmatic skills (e.g., Sykes, Reference Sykes2005), but also that the benefits go beyond improved quantity and quality of language production, with positive effects found for affective, social, and cultural factors (e.g., Müller-Hartmann & Schocker-von Ditfurth, Reference Müller-Hartmann, Schocker-von Ditfurth, Hallet and Königs2010; Yamada & Akahori, Reference Yamada and Akahori2007). Drawing on studies grounded within a task-based framework, as well as those that have examined learning and performance through the use of tasks, this review seeks to bring together the current body of research examining technology and task-based learning, providing an overview of how technology can facilitate and support L2 development and performance in task-based language learning. In addition, this review addresses how technology contributes to our knowledge of TBLT, including the relationship between technology and features of task design and implementation, as well as how computer-mediated contexts can enhance our understanding of the process of L2 learning, including learners’ noticing and negotiation for meaning.
Theoretical Underpinnings of TBLT
In contrast to more traditional, synthetic approaches where language is broken down into decontextualized units to be mastered before learners can correctly apply them in functional real-world situations, TBLT is a process-based approach in which the task is the unit of focus, and where emphasis is placed on interaction, meaning, and what learners can do with language. Having gained a strong foothold as an important pedagogical and methodological approach during the last three decades, TBLT has its roots in Dewey's work on experiential learning, or learning by doing, and what Long (Reference Long2015) referred to as l'education integrale, or whole learning. These philosophical foundations stress the importance of experience and relevance to learning, including the education of the learner for current or future communicative needs via engagement in authentic interactions. In terms of theoretical foundations, TBLT is grounded in a usage-based approach to language acquisition, specifically that of the interaction approach (Doughty & Long, Reference Doughty and Long2003; Long, Reference Long2015). The interaction approach to SLA suggests that conversational adjustments occurring during communication benefit L2 development by providing learners with opportunities to receive modified comprehensible input and interactional feedback, notice gaps between their interlanguage and the target language features, and produce output (Gass & Mackey, Reference Gass, Mackey, Van Patten and Williams2007; Mackey, Abbuhl, & Gass, Reference Mackey, Abbuhl, Gass, Gass and Mackey2012). By providing learners with negotiation opportunities, interaction facilitates acquisition through “the connection of input, internal learner capacities, particularly selective attention, and output in productive ways” (Long, Reference Long, Ritchie and Bhatia1996, pp. 451–452). These negotiations for meaning provide opportunities for learners to identify gaps between their interlanguage and the target language and produce modified output (Gass & Mackey, Reference Gass and Mackey2006; Long, Reference Long, Ritchie and Bhatia1996; Swain, Reference Swain, Gass and Madden1985, Reference Swain, Cook and Seidlhofer1995, Reference Swain and Hinkel2005), thereby offering learners both receptive and productive linguistic benefits. TBLT, then, offers an ideal environment for negotiation, feedback, and output, thereby providing opportunities for L2 development to occur.
TECHNOLOGY AND TBLT
Previous research has proposed a variety of definitions for tasks (see Long, this issue, for a discussion on what is meant by task), ranging from Samuda and Bygate's (Reference Samuda and Bygate2008) operationalization of a task as “a holistic activity which engages language use in order to achieve some non-linguistic outcome while meeting a linguistic challenge, with the overall aim of promoting language learning, through process or product or both” (p. 69) to Long's (Reference Long2015) more recent description of tasks as “the real world activities people think of when planning, conducting, or recalling their day” (p. 6). González-Lloret and Ortega (Reference González-Lloret, Ortega, González-Lloret and Ortega2014) suggested a specific set of criteria for technology-mediated tasks, in which:
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1. The primary focus is on meaning. In other words, learners are focused on the content, including semantic and pragmatic meaning, rather than the form.
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2. Goal orientation is necessary. The task must provide communicative purpose, stimulated by learners’ need to impart information, solve a problem, or express an opinion, as well as a communicative or noncommunicative outcome resulting from task completion. That is, the learners’ use of language is necessary to achieve the desired outcome and is not necessarily the goal in and of itself.
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3. The task should be learner centered, requiring learners to draw mainly on their own linguistic and nonlinguistic resources in addition to their digital skills.
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4. Tasks are authentic and representative of the real world, drawing on real-world processes of language use and integrating form and function.
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5. Opportunities for reflective learning are also provided. This offers learners the chance not only to learn by doing, but also to consider the process as well as the outcome, encouraging cyclical and reflective learning.
Although a number of researchers have highlighted the need to reconsider task design and task-based learning and teaching in light of the unique affordances and features available in computed-mediated contexts (e.g., Chapelle, Reference Chapelle1998, Reference Chapelle2001; Doughty & Long, Reference Doughty and Long2003; Hampel, Reference Hampel2006; Rosell-Aguilar, Reference Rosell-Aguilar2005; Skehan, Reference Skehan2003), the criteria suggested by González-Lloret and Ortega (Reference González-Lloret, Ortega, González-Lloret and Ortega2014) seek to firmly turn the corner on how researchers and educators might best exploit the affordances of technology while incorporating a theoretically and empirically grounded framework. The growing use of technology in the second and foreign language learning classroom underscores the need for the expansion of the definition of task, as the situations in which learners might participate in task-based learning are no longer restricted to a physical classroom. Instead, many learners now have a wide range of tools, including digital game-based learning, mobile-assisted language learning, and place-based learning. In other words, the contexts for learning and the resources available have expanded dramatically over the last few decades. In order to realize the full potential of technology-mediated TBLT, tasks need to be designed not only to promote the need for learners to exchange information, thereby providing multiple opportunities for interaction, and subsequently L2 development, but also to incorporate learners’ digital and technological literacy and proficiency (González-Lloret & Ortega, 2014), acknowledging these areas as resources and skills that also need to be developed to achieve successful task orientation and completion.
TBLT AS A FRAMEWORK FOR CALL
During the last few decades, scholars have sought to not only ground CALL research firmly in SLA theory, but also inform CALL research by drawing on research methods and pedagogical frameworks from instructed SLA (Chapelle, Reference Chapelle1997, Reference Chapelle1998, Reference Chapelle, Egbert and Petrie2005, Reference Chapelle2009). Task-based language learning has served as one such framework, with the guidelines originally set forth by Chapelle elaborated on by first Doughty and Long (Reference Doughty and Long2003) and now González-Lloret and Ortega (Reference González-Lloret, Ortega, González-Lloret and Ortega2014). These criteria and principles provide researchers and educators with guidelines on how to effectively apply task-based learning to the design and implementation of technology-mediated language learning contexts.
Research has since examined the application of these design principles, with studies exploring whether using a task-based framework impacted interaction and learning in CALL contexts. For example, Ortega's (Reference Ortega, Mackey and Polio2009) review addressed the benefits associated with interaction in text-based synchronous computer-mediated communication (SCMC) environment, while Smith (Reference Smith2009) found that task-based activities conducted outside of class led to learners’ subsequent incorporation of input from their interlocutors. Similarly, the findings of González-Lloret (Reference González-Lloret, Soler and Martinez-Flor2008) indicate that this incorporation had a sustained effect on later L2 use, suggesting lasting benefits for technology-mediated task-based work.
TBLT has also been investigated as a pedagogical framework for online language learning courses and tutorials, with the results demonstrating that not only can TBLT provide a useful framework for designing and implementing instructional activities (Duran & Ramaut, Reference Duran, Ramaut and Branden2006; Rosell-Aguilar, Reference Rosell-Aguilar2005), but also that learners and teachers have experienced positive reactions to a task-based approach (Hampel, Reference Hampel2006; Hampel & Hauck, Reference Hampel and Hauck2004). In their examination of TBLT as a pedagogical approach for an ab initio context, Lai, Zhao, and Wang (Reference Lai, Zhao and Wang2011) noted that learners and teachers reacted positively to the task-based approach, with some learners demonstrating improved attitudes toward language learning and improved oral production. The results also indicate that the use of TBLT in this online platform encouraged learners’ participation, reduced their cognitive burden, and provided the instructor with improved opportunities to individualize instruction. Developmental benefits have also been attributed to the use of TBLT as a framework for computer-mediated contexts. For instance, Appel and Gilabert Guerrero's (Reference Appel, Gilabert Guerrero, Macià, Cervera and Ramos2006) investigation of email tandem language learning demonstrated not only that TBLT provided a sound and flexible framework, but also that learners who completed task-based exchanges produced greater and more equitable amounts of language as well as sustained interest and motivation concerning their participation in the exchange. More recently, Nielson (Reference Nielson, González-Lloret and Ortega2014) empirically assessed the effectiveness of a task-based approach for an online Chinese as a foreign language course. The results demonstrate sustained participation rates as well as improved L2 learning outcomes, including gains in speaking proficiency, suggesting that the use of pedagogic tasks and assessment in an online environment had positive effects on learners’ knowledge and experience.
Benefits for incorporating task-based approaches in to other technologies, including multiuser and immersive environments, have also been found. For example, Jauregi, Canto, de Graaff, Koenraad, and Moonen's (Reference Jauregi, Canto, de Graaff, Koenraad and Moonen2011) case study found that the use of a task-based framework led to rich interaction and negotiation among learners in the 3D virtual world of Second Life, a program designed to represent real-life settings, such as campuses or shopping centers, and provide learners with opportunities to interact with other players. In addition, the results indicate great potential for increased awareness of cultural contrasts and similarities through the task-based interactions, although more research is needed to better understand how the specific affordances offered by a virtual online environment can best be exploited in a task-based framework. For example, the Second Life context-specific communicative tasks that were used in this study resulted in lower amounts of interaction, suggesting that tasks should be designed to facilitate interaction while at the same time taking advantage of the functional and gaming possibilities available in this particular context. These results support Peterson's (Reference Peterson2006) findings that task type impacted the quantity and quality of negotiation. Although the results demonstrate that the use of avatars in the 3D virtual world, Active World, supported learners’ negotiation and interaction, learners’ sociocultural concerns also impacted negotiation, suggesting that although CALL contexts might reduce some social and cultural variables, it does not remove them entirely.
Synthetic immersive environments (SIEs), defined as engineered, digital spaces that draw on goal-directed, collaborative gameplay “to produce explicit, educationally related outcomes in simulated, relevant interactional contexts” (Sykes, Reference Sykes2008, pp. 10–11; Sykes, Reference Sykes, González-Lloret and Ortega2014), have also been examined as a potential environment for the application of task-based language learning approaches. Previous research has highlighted how principles of TBLT have been approximated and reflected in task design in digital games (e.g., Salen & Zimmerman, Reference Salen and Zimmerman2004) and SIEs (e.g., Purushotma, Thorne, & Wheatley, Reference Purushotma, Thorne and Wheatley2009), with studies taking into consideration task sequencing, provision of feedback, and the need for learner–learner interaction and negotiation. This body of research demonstrates the potential positive benefits of the use of a task-based framework within the contexts of SIEs, although there is overall little research directly examining how tasks might be designed and assessed in this unique context. Recently, Sykes (Reference Sykes, González-Lloret and Ortega2014) has sought to fill this gap by drawing on 120 hours of in-game behavior data to examine how tasks within the SIE Croquelandia might be effectively designed, implemented, and evaluated.
Although these studies provide promising results regarding the efficacy and practicality of integrating task-based principles into computer-mediated language learning contexts, more research is needed to better understand how TBLT might best be used to maximize the available affordances of technology-mediated learning. As Nielson (Reference Nielson, González-Lloret and Ortega2014) pointed out, technology impacts the entire curriculum, underscoring the importance of using carefully considered guidelines, such as those proposed by González-Lloret and Ortega (Reference González-Lloret, Ortega, González-Lloret and Ortega2014), during the design, implementation, and assessment phases of a task-based approach. In addition, future research should examine how these technology-mediated TBLT principles may be applied to task design and implementation using new and emerging media. Since Lai and Li's (Reference Lai and Li2011) and Thomas’ (2013) reviews of tasks and technology, and despite previous research highlighting the need for explorations of task-based learning in a range of technology-mediated environments (Peterson, Reference Peterson2011), relatively few studies have examined how TBLT might enhance the use of new technologies. Given that technology is a constantly evolving field, more research is needed to understand how the use of task-based principles might guide and enhance the L2 learning potential for digital game-based language learning, mobile-assisted language learning, and learning in social networking and in virtual and immersive environments.
TECHNOLOGY, TASKS, AND SLA
Technology-mediated TBLT offers a fertile environment in which researchers can investigate established constructs of SLA in a still relatively underinvestigated context, with research seeking to establish the ability of technology, specifically CMC, to direct learners’ attention to specific target language features and to provide learners with opportunities to negotiate for meaning, to receive comprehensible input and corrective feedback, and to produce modified output (Smith, Reference Smith2004). In addition, studies have demonstrated the potential for technology to provide additional opportunities for learners to notice target language features, thereby enhancing learners’ potential for L2 development, during task-based interactions.
Negotiation
Descriptive and empirical research has provided compelling evidence that interactional features found to be beneficial to L2 development in face-to-face (FTF) contexts, such as negotiation for meaning and modified output, can and do occur in technology-mediated task-based environments (Beauvois, Reference Beauvois1992; González-Lloret, Reference González-Lloret2003; Iwasaki & Oliver, Reference Iwasaki and Oliver2003; Kötter, Reference Kötter2003; Lee, Reference Lee2001). For instance, tasks commonly found in FTF TBLT research (Pica, Kanagy, & Falodun, Reference Pica, Kanagy, Falodun, Crookes and Gass1993), such as decision-making and information-gap tasks, have been shown to be successful in eliciting learner interaction and negotiation in a CMC environment (Blake, Reference Blake2000; Pellettieri, Reference Pellettieri1999). Studies have also investigated negotiation for meaning, which includes conversational moves such as comprehension checks, confirmation checks, and clarification requests made in response to failures in communication, during SCMC by comparing different communication breakdowns leading to instances of negotiation (Toyoda & Harrison, Reference Toyoda and Harrison2002) and the frequency of negotiation routines when learners interacted with native (Tudini, Reference Tudini2003) or nonnative speaking interlocutors (Fernández-Garcia & Martínez-Arbelaiz, Reference Fernández-Garcia and Martínez-Arbelaiz2002).
Blake (Reference Blake2000) also used communicative text-chat tasks within a computer-mediated environment to encourage negotiation between 50 intermediate learners of Spanish who completed three different types of task, including two-way information-gap tasks. In this type of task, each partner holds half of the information needed for task completion, thereby requiring learners to share and converge on a single-outcome. Learners also completed one-way information-gap tasks (in which only one partner is provided with the relevant information and the other must elicit the data needed for task completion) and decision-making tasks (in which all interlocutors have access to the information needed for task resolution, although they are not required to converge on one single outcome). One-way information-gap tasks were identified as the most effective at promoting negotiation. The results also indicate that learners increased their metalinguistic awareness of their own L2 vocabulary development, suggesting that the benefits of interaction in CMC have communicative as well as potentially developmental benefits.
Similarly, Smith (Reference Smith2003) found that task type plays an influencing role in the ways that learners negotiate for meaning in CMC. Examining 14 learner dyads, Smith examined the amount and types of negotiation occurring when learners encountered novel lexical items during jigsaw and decision-making tasks. Providing additional evidence supporting Pellettieri (Reference Pellettieri, Warschauer and Kern2000), Smith's results demonstrate that learners do negotiate for meaning when miscomprehension occurs in a computer-mediated environment. In addition, the findings provide some evidence that negotiation is affected by type of task, with more negotiation occurring in the decision-making task than the jigsaw task. Although the negotiation patterns identified in this study were similar to those found in FTF environments, Smith argued for an expanded model of negotiation specific to CMC. In contrast to oral contexts, Smith suggested that a CMC model of negotiation must account for the delay between the initial trigger and the following negotiation, as the absence of adjacency turns in text-based chat often leads to extended delays in learners’ responses to negotiation triggers.
The role of type of target feature has also been addressed in CMC contexts, with research finding that, similar to FTF interaction research (Keck et al., Reference Keck, Iberri-Shea, Tracy-Ventura, Wa-Mbaleka, Norris and Ortega2006; Mackey & Goo, Reference Mackey, Goo and Mackey2007), lexical items are more facilitative of negotiation than grammatical items (Blake, Reference Blake2000; Fernández-Garcia & Martínez-Arbelaiz, Reference Fernández-Garcia and Martínez-Arbelaiz2002; Pellettieri, Reference Pellettieri, Warschauer and Kern2000; Tudini, Reference Tudini2003). For example, Pellettieri (Reference Pellettieri, Warschauer and Kern2000) found that a greater number of communication problems triggering negotiation occurred over lexical items than grammatical items, with the same results reported by Tudini (Reference Tudini2003). In addition, de la Fuente's (Reference de la Fuente2003) results indicate that learners in both FTF and CMC negotiated interaction groups demonstrated greater comprehension on lexical items than learners in a nonnegotiated interaction group, and in results similar to those by Pellettieri (Reference Pellettieri, Warschauer and Kern2000), Blake (Reference Blake2000) found that these negotiations were most often triggered by lexical items, with 75% and 95% of all negotiations occurring in response to lexical misunderstandings.
Research has also examined the effect of specific types of technology on the quantity and type of negotiation learners produce, with studies comparing the amount of negotiated repair moves in voice and text-chat (Jepson, Reference Jepson2005) and the relationship between negotiated interaction and the use of scrolling or cursor movement (Smith, Reference Smith2009). Wang (Reference Wang2006) examined the role of visual cues, such as facial expressions or gestures, in negotiation routines during video conferences, finding that although video conferencing contained unique features of interaction, beneficial negotiation and focus on form also occurred. Taking an ethnographic approach, Zheng, Li, and Zhao (Reference Zheng, Li and Zhao2008) also found evidence of negotiation for meaning for learners participating as avatars in the virtual world of Second Life. The results of Zheng et al. (Reference Zheng, Li and Zhao2008) demonstrate not only that learners can and do negotiate for meaning in this virtual world, but that they are also highly engaged in the game as well as the interaction.
A variety of studies have compared the impact of different computer-mediated methods on L2 development (e.g., Lo, Wang, & Yeh, Reference Lo, Wang and Yeh2004; Ma, Van Vosselen, Gierts, & Vandamme, Reference Ma, Van Vosselen, Gierts and Vandamme2002; Smith, Alvarez-Torres, & Zhao, Reference Smith, Alvarez-Torres and Zhao2003; Yanguas, Reference Yanguas2010, Reference Yanguas2012), with the results revealing interesting differences across mode on L2 learning outcomes. For example, Jepson (Reference Jepson2005) found that a higher number of repair moves occurred in voice chat than text-chat, whereas Yanguas (Reference Yanguas2010) found advantages for an audioconferencing group over both video and FTF. Specifically, Yanguas (Reference Yanguas2010) found differences in negotiation patterns between learners participating in audio interaction with learners taking part in FTF or video interaction, a difference attributed to the lack of visual input in the audio SCMC group. Learners in the audio group seemed to utilize other linguistic resources when deprived of the visual cues in video SCMC and FTF contexts. The results also indicate that overall interactional patterns in oral SCMC were more similar to those found in FTF contexts than those of written CMC, suggesting that there are important implications of restricting learners’ input to aural or literal forms. Advantages for audio SCMC contexts over video SCMC or FTF contexts have also been found on listening comprehension measures (Yanguas, Reference Yanguas2012), suggesting that there may be positive benefits to audio conferencing for oral measures over other forms of SCMC. In addition, written SCMC may require more verbal explicitness due to the lack of visual contact, thereby drawing learners’ attention to form in the input and their subsequent output.
Researchers have argued that video SCMC provides similar social signals as FTF interaction, as learners are still able to receive and produce visual and situational cues (Lee, Reference Lee2007). Similarities in performance have been found for learners in video SCMC and FTF contexts, although these similarities do not seem to extend to audio SCMC interaction, highlighting the need for further research investigating the effects of different modalities of leaners’ patterns of negotiation and feedback. It is also important that researchers keep in mind that that negotiations conducted in SCMC contexts are likely to experience potentially extended delays between triggers and indicators (Smith, Reference Smith2003), and that these temporal restrictions may have important implications. For instance, there is a short time delay in text-chat between the initiation of the utterance and its receipt by the interlocutor. More importantly, SCMC does not adhere to the same pattern of turn adjacency found in FTF interaction. Rather, negotiation triggers may be followed by an indicator, but are initially unaddressed, only to be answered later after a repeat indicator in subsequent turns. These delays between triggers, indicators, and responses, referred to as split negotiation routines (Smith, Reference Smith2003), highlight the possibility that negotiation and its associated benefits may be hampered by time restrictions due to the complex nature of interaction in SCMC.
Although there are similarities in when and how negotiation occurs in FTF and computer-mediated contexts, it is important that researchers and educators keep in mind that there are also important differences, such as variations in triggers and patterns. However, more research is needed to expand our knowledge of how patterns of interaction may vary across individual technologies. Research has demonstrated the existence of unique patterns of negotiation and turn taking in written text-chat (Smith, Reference Smith2003), highlighting the need for additional investigations in to whether learners participating in mobile-assisted or multiuser gaming or immersive environments interact in unique ways. Future research should consider how type of technology mediates the quantity and quality of interaction during task-based learning and teaching. In general though, research suggests that negotiation, and its associated benefits, seem to be available to learners in computer-mediated task-based interactions, providing evidence for the efficacy of technology in task-based contexts.
Noticing
Schmidt's noticing hypothesis (Schmidt, Reference Schmidt and Robinson2001; Schmidt & Frota, Reference Schmidt, Frota and Day1986) emphasizes the importance of noticing, specifically noticing of the formal features in the target language, as well as noticing gaps between a learner's interlanguage and the target language. According to this hypothesis, noticing is a necessary condition of SLA, with empirical studies demonstrating a direct link between the noticing of a target feature and its subsequent intake (Izumi, Reference Izumi2002; Izumi, Bigelow, Fujiwara, & Fearnow, Reference Izumi, Bigelow, Fujiwara and Fearnow1999; Leow, Reference Leow2001; Mackey, Gass, & McDonough, Reference Mackey, Gass and McDonough2000; Mackey, Philp, Egi, Fujii, & Tatsumi, Reference Mackey, Philp, Egi, Fujii, Tatsumi and Robinson2002). Research on tasks and technology suggests that computer-mediated contexts may promote the noticing of forms and gaps between learners’ interlanguage and target language, underscoring the potential benefits for L2 development due to the increased number of noticing opportunities afforded to learners. For instance, Pellettieri's (Reference Pellettieri, Warschauer and Kern2000) results indicate that text-chat promoted learners’ use of negotiation of meaning and form-focused interaction, leading her to argue that the additional time for monitoring and processing in SCMC supported learners’ noticing of gaps, thereby facilitating their L2 development. The unique characteristics of SCMC, specifically within the written mode of text-chat, provide learners with visual saliency, chances to review the output of both interlocutors, and longer times for processing and planning production (Beauvois, Reference Beauvois1992; Pellettieri, Reference Pellettieri1999, Reference Pellettieri, Warschauer and Kern2000; Smith, Reference Smith2004, Reference Smith2005; Smith & Gorsuch, Reference Smith and Gorsuch2004; Warschauer, Reference Warschauer1996, Reference Warschauer1997), thereby increasing the opportunities that learners have to focus on form and providing improved chances for L2 development (Salaberry, Reference Salaberry2000). For example, Yilmaz and Yuksel (Reference Yilmaz and Yuksel2011) found that recasts in written text-chat yielded improved performance when compared to FTF task-based interaction, suggesting that the use of technology may have reduced the cognitive burden on learners during the task, thereby freeing up attentional resources to take advantage of noticing opportunities.
These proposed advantages for processing, noticing, and focus on form are particularly true of text-chat exchanges, as learners are presented with a written record of the interaction, which may provide added opportunities for learners to attend more closely to the form and content of the input, while still maintaining the real-time feel of conversation (Pellettieri, Reference Pellettieri, Warschauer and Kern2000; Smith, Reference Smith2003; Toyoda & Harrison, Reference Toyoda and Harrison2002). Because learners are afforded the ability to review chat logs or transcripts, this may provide learners with additional opportunities to reflect on the discourse (Beauvois, Reference Beauvois1992), to notice new target items as well as the gaps in their interlanguage (Kelm, Reference Kelm1992), and enhance incidental noticing (Warschauer, Reference Warschauer1997). Toyoda and Harrison (Reference Toyoda and Harrison2002) suggested that by providing learners with the opportunity to visually review their interaction through chat logs, such as through posttask monitoring, their attention will be directed to their interlanguage, thereby potentially leading to improvement.
These potential benefits of SCMC are not limited to posttask, however. For example, Payne and Whitney (Reference Payne and Whitney2002) found that learners reported noticing their mistakes more frequently during tasks conducted in SCMC chat environments than in FTF interaction. Similarly, through the use of stimulated recalls, Lai and Zhao (Reference Lai and Zhao2006) found that text-chat resulted in learners’ improved noticing of errors and interactional feedback, while Smith and Gorsuch's (Reference Smith and Gorsuch2004) study examining the relationship between learners’ verbalizations, gestures, and scrolling, found an increased attention to form. The results of Shekary and Tahririan's (Reference Shekary and Tahririan2006) research indicate a greater occurrence of language-related episodes (LREs), as well as improved learning of the linguistic items that were discussed during task performance. More recently, Smith (Reference Smith and Hult2010, Reference Smith2012) used eye-tracking technology to examine the relationship between recasts, noticing, and uptake, providing tangible evidence of what learners’ attended to in the input and the feedback that was provided during task performance. Seeking to obtain more insight into the learning process, Yuksel and Inan (Reference Yuksel and Inan2014) used stimulated recall protocols to examine instances of negotiation for meaning and noticing in both SCMC and FTF task-based interactions, finding that although more negotiation occurred in FTF, learners in the SCMC environment noticed these instances of negotiation significantly more than those in the traditional oral context. These studies also demonstrate the variety of methods used to measure noticing, including eye tracking to measure eye gaze duration (e.g., Smith, 2012, Reference Smith2012), stimulated recall (e.g., Gurzynski-Weiss & Baralt, Reference Gurzynski-Weiss and Baralt2014a, Reference Gurzynski-Weiss and Baralt2014b; Lai, Fei, & Roots, Reference Lai, Fei and Roots2008; Lai & Zhao, Reference Lai and Zhao2006; Smith, Reference Smith and Hult2010; Yuksel & Inan, Reference Yuksel and Inan2014), think-alouds (Lai et al., Reference Lai, Fei and Roots2008), and LREs (Shekary & Tahririan, Reference Shekary and Tahririan2006).
In addition to potentially increasing learners’ opportunities for noticing, SCMC may help draw learners’ attention to formal features within the input. For instance, Pellettieri (Reference Pellettieri1999) found that 50% of students said they focused more on form in text-chat than in FTF, suggesting that text-based SCMC provides learners with opportunities for increased monitoring and noticing of their own and their interlocutor's production. Empirical research has also demonstrated that SCMC may encourage learners to focus on form (Blake, Reference Blake2000; Salaberry, Reference Salaberry2000; Shekary & Tahririan, Reference Shekary and Tahririan2006), as well as potentially enhance negotiation for form and meaning (Lee, Reference Lee2002).
Although SCMC has been argued to enhance the salience of target forms (Smith, Reference Smith2004, Reference Smith and Hult2010), research in this area could be expanded (although see Yilmaz, Reference Yilmaz2012), emphasizing the need for further investigations into the role of salience and complexity of target items at enhancing or mitigating the positive effects of task-based interaction. In addition, not all studies have found support for the efficacy of SCMC in promoting noticing, with some research demonstrating no differences between traditional and technology-mediated task-based interaction (Gurzynski-Weiss & Baralt, Reference Gurzynski-Weiss and Baralt2014b). Gurzynski-Weiss and Baralt (Reference Gurzynski-Weiss and Baralt2014a) examined whether type of modified output predicted learners’ correct noticing of feedback in computer-mediated and FTF contexts. Their results indicate that modified output, both partial and fully modified, strongly predicted learners’ accurate noticing of feedback. Although there were no significant differences across mode, partial modified output was a much greater predictor in SCMC than in FTF, suggesting that the available opportunities for comparing interlanguage and target language and juxtaposing feedback and erroneous utterances are likely to enhance noticing and cognitive integration.
Although the results are somewhat mixed, taken together these findings provide substantial support for the use of technology in supporting and facilitating noticing, thereby providing learning and development opportunities. In addition, these studies demonstrate some of the potential methodological advantages that might be available in technology-mediated TBLT. For example, by using multiple technologies, including screen capture to observe scrolling and mouse behavior, eye tracking, and stimulated recall based on multimedia stimuli, researchers have multiple methods to measure SLA constructs like noticing. In addition, multiple methods should be used to provide a range of perspectives and, importantly, to triangulate evidence. Future research should seek to take advantage of these methods in order to deepen our understanding of how and what learners might be attending to during various phases in task-based learning.
Affective Factors and Individual Differences
Recently, González-Lloret and Ortega (Reference González-Lloret, Ortega, González-Lloret and Ortega2014) suggested that technology-mediated tasks may reduce learners’ anxiety and increase their motivation and creativity, as well as promote more engagement and participation. Indeed, previous research seems to support these claims, with studies demonstrating that SCMC may result in increased and more equitable learner participation (Beauvois, Reference Beauvois1992; Kelm, Reference Kelm1992; Kern, Reference Kern1995; Warschauer, Reference Warschauer1996), as well as greater quality of language production (Chun, Reference Chun1994; Kelm, Reference Kelm1992; Kern, Reference Kern1995; Warschauer, Reference Warschauer1996), than in FTF interaction. In addition, CMC may result in greater amounts of learner output (Chun, Reference Chun1994; Kelm, Reference Kelm1992) and may also provide learners with a less stressful environment than FTF interaction (Chun, Reference Chun1998), potentially leading to reduced anxiety and improved willingness to communicate.
Studies have suggested that one of the benefits of computer-mediated interaction is the potential to reduce learners’ anxiety levels (Chun, Reference Chun1994; Kelm, Reference Kelm1992; Kern, Reference Kern1995; Warschauer, Reference Warschauer1996), because, as Beauvois (Reference Beauvois1992) pointed out, the reduced sense of immediacy may provide learners with additional time to process input and produce output. This added time may be beneficial to learners with greater levels of anxiety or for learners with low proficiency levels, as learners are provided with additional opportunities to reflect on what was said before responding (Beauvois, Reference Beauvois1992), thereby theoretically reducing their levels of anxiety (Baralt & Gurzynski-Weiss, Reference Baralt and Gurzynski-Weiss2011). However, there remains very little empirical evidence examining state anxiety across modality, with much of the previous research having focused on self-report and perception data. Seeking to provide a more objective perspective, Baralt and Gurzynski-Weiss (Reference Baralt and Gurzynski-Weiss2011) found no differences in state anxiety between FTF and CMC, although learners’ perceptions of CMC remained positive. Given that many scholars have hypothesized the benefits of technology to mediate affective factors, the paucity of empirical research in this area highlights the need for more research investigating the extent that technology might affect learners’ anxiety, as well as their subsequent L2 development and performance.
Studies have also suggested that more introverted learners may feel more comfortable participating in electronic conversations with their peers when some of the social pressures of FTF communication are removed, allowing them to produce and participate more equally in interactions (Kern, Reference Kern1995; Warschauer, Reference Warschauer1996). For example, Kern (Reference Kern1995) found that introverted learners may be more likely to participate in SCMC contexts, with students indicating on self-report measures that they “freer” to take part in the task-based interaction. In other words, learners in SCMC interactions may participate more often and more equally than learners in FTF environments (Fitze, Reference Fitze2006; Kern, Reference Kern1995; Kitade, Reference Kitade2000), promoting increased participation by less active students when compared with more active, dominating students (Chun, Reference Chun1994; Warschauer, Reference Warschauer1996). In addition, studies show that SCMC leads to increased individual practice time (Bueno-Alastuey, Reference Bueno-Alastuey2011), thereby offering learners opportunities to share the control and direction of the interactive task. Furthermore, without the pressure of the social or pragmatic cues present in FTF interaction, learners may be freer to focus on language and meaning (Yamada & Akahori, Reference Yamada and Akahori2007). The absence of this input may also provide learners with opportunities to test hypotheses about the target language without social pressure (Payne & Whitney, Reference Payne and Whitney2002) or encourage students’ risk-taking regarding language (Meunier, Reference Meunier and Muyskens1998).
Research has also explored the impact of technology on learners’ motivation, with recent research by Murphy (Reference Murphy and Morrison2011) demonstrating the importance of corrective feedback provided during social interaction in asynchronous and synchronous chats and its role on learners’ motivation during task performance. The results suggest that feedback contributed to learners’ improved confidence and self-evaluation, while the social aspects served as a source of motivation for students, thereby showing the positive impact of CMC on affective factors. Similarly, Sadler and Nurmukhamedov (Reference Sadler and Nurmukhamedov2008) found that task-based activities conducted in the context of Second Life sustained learners’ motivation and resulted in negotiation and interaction. Case studies have also found that the unique context of a technology-mediated environment may provide learners with opportunities to construct positive L2 identities (see Thorne, Sauro, & Smith, Reference Thorne, Sauro and Smith2015, for a review of technology and identity), thereby supporting autonomy and agency, constructs that are linked to motivation and engagement (e.g., Deci & Ryan, Reference Deci and Ryan2002). For example, Lam (Reference Lam2000, Reference Lam2004) found that learners’ participation in online task-based environments led to the creation of new identities that varied from the social categories and norms of their local real-world context. Fandom, the online networks of fans that develop around a specific aspect of popular culture, has also provided researchers with a unique environment in which to explore how learners exploit various aspects of social, textual, and technological features to engage in identity creation (Black, Reference Black2006) and the advancement of linguistic skills (Sauro, Reference Sauro, González-Lloret and Ortega2014).
Overall, these findings demonstrate the potential for dynamic technologies to provide an engaging learning context grounded in problem solving, collaboration, and social interaction, rather than the format of information presentation found in more traditional instruction, thereby providing support for learners’ motivation, autonomy, confidence, and willingness to communicate. Many of these studies, however, have relied on qualitative, anecdotal evidence or learner self-report questionnaires, providing only a partial picture of the role of these important constructs in technology-mediated TBLT. In order to more comprehensively assess the relationship between affective factors and technology-mediated task-based learning, quantitative instruments should be implemented in addition to perception measures. The use of quantitative measures, such as surveys with Likert scale–type questions, will generate descriptive measures and facilitate correlational analyses between learner performance, development, and affective factors, providing important information regarding the effects across mode and setting. Future research should consider the use of multiple methods to provide a more holistic, and complete, understanding of whether technology-mediated contexts support or constrain affective factors, like anxiety, motivation, and willingness to communicate, during task-based interactions.
Technology, Tasks, and L2 Learning Outcomes
Previous research has demonstrated the potential benefits of technology-mediated TBLT not only for L2 linguistic skills, such as oral proficiency (e.g., Payne & Whitney, Reference Payne and Whitney2002) and comprehension (e.g., Yanguas, Reference Yanguas2012), but also for cultural understanding (e.g., Darhower, Reference Darhower2002) and pragmatic development (e.g., Sykes, Reference Sykes2005).
SCMC in particular has yielded a large body of research demonstrating the efficacy of written text-chat for promoting a range of language learning outcomes. For instance, Smith (Reference Smith2004) found that dyads participating in task-based interaction in an SCMC environment experienced significant gains on a vocabulary test, while Sauro's (Reference Sauro2009) results show that corrective feedback delivered during SCMC interactions led to improvement in learners’ grammatical competence. Pellettieri (Reference Pellettieri, Warschauer and Kern2000) also suggested that synchronous text-chat may be more beneficial to learners’ L2 development than FTF contexts, as it provides learners with a visual representation of their own output, thereby directing learners’ attention to their language and allowing students to “practice and gain control over more cognitively demanding aspects of grammar that otherwise might not be so frequently practiced in classroom oral interaction” (p. 82). De la Fuente's (Reference de la Fuente2003) results also illustrate these claims, as learners participating in written SCMC outperformed learners participating in FTF interaction on written measures of production and recognition. These visual features have been argued to promote the production of more complex (Böhlke, Reference Böhlke2003; Kern, Reference Kern1995; Kitade, Reference Kitade2000; Warschauer, Reference Warschauer1996) and accurate (Salaberry, Reference Salaberry2000) language, as well as improvements in the quantity and quality of pragmatic strategies (Sykes, Reference Sykes2005). Research has also found opposite trends, however, with Böhlke (Reference Böhlke2003) and Pyun (Reference Pyun2003) finding reduced complexity in learners’ language, although this variation may be due to differences in coding and analysis rather than modality. In addition, Sauro (Reference Sauro2012) found no differences across modalities, instead finding variation across types of learners, suggesting that individual learner differences may play a more substantial role than has been investigated.
The potential benefits of technology are not limited to synchronous task-based interaction, however, with research demonstrating the impact of tasks performed in an asynchronous computer-mediated communication (ACMC) environment on learning outcomes. For example, studies have explored learning outcomes following collaborative writing tasks in a wiki, finding evidence of increased creativity and complexity of learners’ production (Mak & Coniam, Reference Mak and Coniam2008). Learners’ participation in blogging has also demonstrated positive findings, such as more grammatically and lexically complex language (Hwang, Reference Hwang2008; Sotillo, Reference Sotillo2000) and improved grammatical accuracy (Murray & Hourigan, Reference Murray and Hourigan2008) and fluency (Lee, Reference Lee2010). Additionally, learners’ cultural competence has improved as a result of participation in task-based learning in blogging (Ducate & Lomicka, Reference Ducate and Lomicka2008; Elola & Oskoz, Reference Elola and Oskoz2008, Reference Elola and Oskoz2010) and collaborative writing using wikis (Wang, Zou, Wang, & Xing, Reference Wang, Zou, Wang and Xing2013).
However, despite the positive results associated with TBLT in both SCMC and ACMC, few studies have focused on whether the combination of multiple tools might further enhance the associated development benefits. Initial explorations of multimodal learning contexts focused on the suitability, design, and implementation of tasks, finding that environments integrating more than one type of technology can and do provide learners with opportunities to receive and provide feedback, to focus on form, and for L2 development (Hampel, Reference Hampel2006; Wang, Reference Wang2006). Collaborative writing combined with chat technology has also yielded interesting results, with learners focusing on different aspects of language depending on the synchronicity of the interaction (Elola & Oskoz, Reference Elola and Oskoz2010). When using SCMC, learners tended to focus more on content and meaning construction, whereas when engaged in writing using ACMC, learners attended to grammar and self-monitoring (Oskoz & Elola, Reference Oskoz, Elola, González-Lloret and Ortega2014), suggesting that the use of these multiple modalities provided learners with a range of opportunities to exploit the affordances available to them, leading to positive benefits on their complexity and accuracy. Lee and Markey (Reference Lee and Markey2014) also investigated the use of multiple technologies, namely, social media, blogs, and podcasts, on learners’ intercultural competence and development. Their findings indicate that learners not only felt that the technology positively affected their interaction, but that they gained cultural knowledge about the target culture and were encouraged to reevaluate their beliefs about their own culture. Furthermore, improvements in learners’ lexical knowledge and discourse were noted. These findings also point to the tremendous potential provided by multiple technologies. In other words, multimodal contexts offer learners opportunities to make choices and take control of not only which tools they elect to use, but also how to take advantage of the various features of the available technology to successfully complete the task at hand (Kenning, Reference Kenning2010).
Although benefits may vary across technologies, there is a growing body of evidence that the use of technology in task-based learning environments has a positive impact on a wide range of learning outcomes. However, more research is needed to explore the potential benefits of new and underrepresented technologies. For example, despite the availability of video-chat programs such as Skype and Google Hangouts, there has been relatively little research conducted using audio and video modalities (e.g., Bueno-Alastuey, Reference Bueno-Alastuey2011, Reference Bueno-Alastuey2013; Jepson, Reference Jepson2005; Sykes, Reference Sykes2005; Yanguas, Reference Yanguas2010, Reference Yanguas2012). In addition, although interest in the use of gaming and multiuser environments has grown (Aldrich, Reference Aldrich2009; Thorne, Black, & Sykes, Reference Thorne, Black and Sykes2009), there are only a small number of studies examining task-based L2 performance and development in virtual or immersive environments (e.g., Peterson, Reference Peterson2006; Sykes, Reference Sykes, González-Lloret and Ortega2014; Zheng et al., Reference Zheng, Li and Zhao2008). Overall, then, various technologies seem to provide learners with a range of opportunities to benefit from task-based interaction, although more research should be done in order to better our understanding of how these technologies, both individual and combined, can best facilitate and support L2 learning outcomes in task-based learning and teaching.
TASK DESIGN, IMPLEMENTATION, AND LEARNERS’ PERFORMANCE
The emergence of TBLT as a leading research and pedagogical framework has yielded a large body of work on empirical investigations of the different factors that might impact learners’ task performance, including variations in task design and task implementation in terms of complexity, sequencing, repetition, and planning. Although the majority of this research has been conducted in traditional FTF contexts, explorations of these factors in computer-mediated environments are increasing.
Task Complexity and Sequencing
As TBLT has grown during the last three decades, understanding the effects of task complexity on L2 development has become more relevant for educators and researchers. However, despite the substantial attention this issue has received in FTF environments (e.g., Gilabert, Barón, & Llanes, Reference Gilabert, Barón and Llanes2009; Kim, Reference Kim2012; Nuevo, Reference Nuevo2006; Révész, Reference Révész2009, Reference Révész2011), very few studies have examined this claim within the context of technology-mediated TBLT. Following a pretest-posttest-delayed posttest design, Baralt (Reference Baralt2013) examined the effects of simple versus complex tasks in FTF and SCMC interactions. Baralt's results indicate that increases in cognitive complexity led to increased L2 development in the FTF context, while the simple task led to better results within the SCMC interactions. These findings, which are similar to Nik's (Reference Nik2010) results indicating that simple tasks in SCMC led to improved accuracy, suggest that complex tasks may not facilitate L2 learning in SCMC in the same way that they do in FTF contexts, possibly due to the noncontingency of feedback episodes (Baralt, Reference Baralt2013). Adams, Nik, and Newton (Reference Adams, Nik and Newton2015) also found that task complexity affected the accuracy but not the complexity of learners’ production in SCMC contexts, findings that fail to meet the predictions set forth by the cognition hypothesis (Robinson, Reference Robinson2001). Because much of the research on task complexity is situated within the framework of Robinson's cognition hypothesis, whose central claim is that cognitive complexity should serve as the determining factor for the sequencing of simple and complex tasks, it is necessary to also investigate sequencing in a computer-mediated learning context.
Extending previous research, Baralt (Reference Baralt, Baralt, Gilabert and Robinson2014) investigated the effects of differential sequencing of cognitively simple and complex tasks on learners’ opportunities for learning and their subsequent L2 development. Following a repeated measures design, all learners completed various sequences of simple and complex story retelling tasks, providing a more in-depth examination of the effects of complex, simple, and U-shaped sequences (Robinson, Reference Robinson and Robinson2011). To explore the degree to which complexity influenced learners’ collaborative learning opportunities of the target structure, the chat and oral transcripts were coded for LREs involving the Spanish past subjunctive. Development was measured in terms of learners’ use of the target structure on written and oral production tasks. The results indicate that learners in the computer-mediated context did not produce any LREs regardless of the sequencing of the tasks, while those participating in FTF tasks produced significantly different amounts of LREs according to the various task sequences. These findings suggest that the modality may have played a substantial role in learners’ willingness to discuss the use of the target structure. Furthermore, learners participating in the online classroom environment failed to produce the target structure on the oral or written production posttests. Overall then, Baralt (Reference Baralt, Baralt, Gilabert and Robinson2014) found no positive effects for complexity or sequencing in the online environment, nor was there any evidence of LREs during SCMC.
Adams and Nik (Reference Adams, Nik, González-Lloret and Ortega2014) examined the impact of prior knowledge, one of the influential cognitive factors identified by Robinson's (Reference Robinson2001, Reference Robinson2005) cognition hypothesis, on the complexity, accuracy, quantity, and distribution of learners’ production in written text-chat. The results are contrary to the predictions of the cognition hypothesis, in that increased task complexity led to increased lexical complexity and overall accuracy, whereas decreasing task complexity resulted in greater production during task performance. Similarly, Nik, Adams, and Newton (Reference Nik, Adams and Newton2012) found that increasing task complexity led to a reduction in interactional modifications during SCMC tasks, providing support for previous research suggesting that task design features may play a very different role in technology-mediated contexts than in traditional classroom formats (e.g., Baralt, Reference Baralt2013; Ortega, Reference Ortega, Mackey and Polio2009).
Taken together, these results demonstrate that predictions of the role of task complexity and task sequencing may not be borne out in technology-mediated TBLT as they are in traditional FTF contexts. These differences may be due to the availability of additional time for planning and processing in technology-mediated tasks, as learners have the ability to monitor production before transmission, potentially mitigating any differences between simple and complex tasks in terms of performance, particularly complexity and accuracy (Adams & Nik, Reference Adams, Nik, González-Lloret and Ortega2014). However, in order to investigate this empirically, it is critical that researchers employ screen-capture software to record not only what learners produce and transmit, but also what they produce and delete or revise. By using video-enhanced chatscripts (Sauro & Smith, Reference Sauro and Smith2010), researchers can gain valuable insight into learners’ process of production and the amount and context in which reformulations occur. As has also been pointed out in previous reviews (e.g., Lai & Li, Reference Lai and Li2011), these studies highlight the need for task-based researchers to consider the use of technology as an additional task design feature that may increase the complexity of the task simply through its application in an online environment. Learners’ digital literacy and technological familiarity may themselves be competencies in need of support (González-Lloret & Ortega, Reference González-Lloret, Ortega, González-Lloret and Ortega2014), as they are unique to the context of SCMC and may influence how learners interact with their interlocutors as well as the tasks.
Task Repetition
Another task implementation feature that has received relatively little attention in computer-mediated contexts is that of task repetition. By providing learners with opportunities to process and attend to content, form, and/or meaning during the initial exposure, repetition has been proposed to support language learning by freeing up attentional resources for during-task performance. To date, few studies have directly examined task repetition in a technology-mediated context (although some might argue that the opportunity to complete a task before performing it again is a type of task planning [Ellis, Reference Ellis2009], studies examining repetition or rehearsal are discussed here rather than under the heading of planning).
Park (Reference Park2008) examined the effects of task repetition on the quantity, defined as the number of words produced by each participant in each task, and quality of learners’ production, operationalized through syntactic complexity, overall accuracy, and amount of negotiation for meaning. No significant differences were found for complexity or accuracy. The results also indicate that task repetition led to a decrease in the amount of negotiation, as well as decreased production, although this finding could also be explained by other factors, such as learners’ typing speed. In addition, it is important to note that in this study, tasks were repeated a week after the initial exposure, potentially constraining any cognitive benefits that learners may have gained from the repetition. In other words, the amount of time that passed between the first exposure and the repetition of the task may have negated the positive effects for prior processing hypothesized to be a benefit of task repetition (Bygate, Reference Bygate, Bygate, Skehan and Swain2001). In addition, dyads were not consistent, which may also have played an important role in the quantity and quality of learners’ production.
More recently, Liao and Fu (Reference Liao and Fu2014) explored the impact of task repetition on learners’ complexity, accuracy, and fluency in written text-chat. Although the results indicate that task repetition improved the syntactic and lexical complexity of learners’ production, the units used to measures these constructs may not have captured all of the nuances available to the researchers in this context. For example, simple type-token ratio was used to assess lexical complexity, an approach that has been criticized for failing to capture the impact of text length (Hsu, Reference Hsu2012). In addition, T-units were used to examine production due to their focus on written language. However, as has been pointed out by previous research (e.g., Sauro, Reference Sauro2012), SCMC exhibits many of the features of spoken language and may be better captured by the AS-unit (Foster, Tonkyn, & Wigglesworth, Reference Foster, Tonkyn and Wigglesworth2000) rather than a T-unit or C-unit. The use of the T-unit in this case may have resulted in a large amount of unanalyzable language, that is, language that was not captured by the constraints of the T-unit, thereby providing a potentially skewed assessment of the impact of repetition on learners’ production.
Although these studies have made important first steps in examining an underresearched area at the intersection of tasks and technology, there are a number of methodological improvements that could be made to provide more robust results. Thus, it is recommended that the results of these studies should be interpreted with caution. Overall, the paucity of studies examining task repetition in technology-mediated TBLT highlights the need for further investigations; particularly those with sound methodological and design features.
Pretask and During-Task Planning
Although research has demonstrated that planning time provides learners with opportunities to formulate, organize, and mentally store content, thereby freeing up attentional resources during tasks (Skehan, Xiaoyue, Qian, & Wang, Reference Skehan, Xiaoyue, Qian and Wang2012), there are currently only a handful of studies examining pre- and during-task planning in computer-mediated contexts (Hsu, Reference Hsu2012, Reference Hsu2015; Lai et al., Reference Lai, Fei and Roots2008; Sauro, Reference Sauro2012; Sauro & Smith, Reference Sauro and Smith2010; Ziegler, under review; Ziegler & Mackey, Reference Ziegler and Mackey2014). Scholars have argued that SCMC provides increased time for during-task processing and planning (Sauro, Reference Sauro2009), which in turn may support noticing and focusing on form, and empirical evidence seems to suggest that learners do in fact take advantage of the additional processing time afforded them in SCMC to take part in online planning and postproduction monitoring. For example, in their study of learners of German as a foreign language, Sauro and Smith (Reference Sauro and Smith2010) found that learners use online planning time to monitor their production and that of their interlocutors, resulting in more careful production and complex language.
In response to suggestions that learners should be encouraged to plan before participating in computer-mediated tasks (Skehan, Reference Skehan2003), researchers have also sought to examine the effects of pretask planning. For instance, Lai et al. (Reference Lai, Fei and Roots2008) investigated whether the provision of 10 minutes of written pretask planning time would impact learners’ noticing of recasts during SCMC tasks. The findings demonstrate that prewriting significantly affected learners’ noticing of contingent recasts, suggesting that planning may have helped to draw learners attention to the gap between their production and the target language. Hsu (Reference Hsu2012) also examined the influence of 10 minutes of pretask planning time on learners’ complexity, accuracy, and fluency during computer-mediated task-based interaction, with the results indicating no differences between the no planning and planning condition. Hsu hypothesized that this may have been due to the unlimited amount of during-task planning time, as learners in the no-pretask planning group may have simply taken advantage of the ample during-task time to monitor their production.
Building on these findings, Hsu (Reference Hsu2015) explored the effects of pretask planning time in the form of rehearsal, combined with unlimited during-task planning, in comparison to unlimited during-task planning only. Learners completed four picture narrative tasks: two as experimental tasks and two as new tasks to investigate subsequent development. The results indicate that both conditions led to immediate improvements in complexity, but the pre- and during-task planning condition resulted in increased complexity and accuracy on the delayed tasks. Finally, Ziegler (under review) explored how differential pretask planning times would influence learners’ complexity, accuracy, and fluency in L2 text-chat. The results indicate that 3 minutes of planning time resulted in greater lexical complexity when compared to no pretask planning time or 1 minute of pretask planning time. No differences were found for other measures of complexity, accuracy, or fluency. Taken together, these studies present mixed results regarding the benefits of pretask planning in written text-chat, highlighting the need for further research in this area.
Overall, more research is needed to investigate the differential effects of task design features (e.g., task complexity) and task implementation (including sequencing, planning, and repetition). Very little research examining such frameworks as the cognition hypothesis and tradeoff hypothesis, as well as how tasks might be sequenced in order to optimize L2 learning opportunities (e.g., the SSARC model; Robinson, Reference Robinson, Pütz and Sicola2010), has been conducted in technology-mediated task-based contexts, highlighting the need for researchers to consider how modality might mediate, support, or constrain the benefits of these factors.
CONCLUSION
This article sought to review the relationship between TBLT and technology, highlighting the potential developmental and performance benefits offered by the use of technology in task-based contexts, as well as the contributions that a task-based framework might make to computer-mediated language learning environments. The use of technology in the classroom continues to increase, underscoring the need for methodologically sound, well-grounded, relevant research that can be used to conscientiously inform pedagogical practice. Technology-mediated TBLT provides an ideal framework in which technology and tasks provide great potential for a mutually beneficial relationship, although more research is needed to understand how new and emerging technologies, or the combination of multiple technologies, impact task-based learning. For example, much of the research on the efficacy of technology-mediated tasks has been conducted in written text-chat, with fewer studies examining multimodal or immersive environments, although these areas of research are growing. Positive effects have also been found for socially oriented technologies (Wang & Vásquez, Reference Wang and Vásquez2012), mobile-assisted language learning (Burston, Reference Burston2015), and simulations and gaming (Peterson, Reference Peterson2006), with the findings indicating that the use of meaningful and engaging games may lead to greater L2 learning outcomes than games incorporating traditional drill-and-practice approaches (Chiu, Kao, & Reynolds, Reference Chiu, Kao and Reynolds2012). Digital game-based language learning has been highlighted for its flexibility and potential to maintain student interest in language learning (Blake, Reference Blake2011), as designers can choose to incorporate both traditional, practice-based learning and the unique affordances provided by social computing, while socially oriented technologies have been praised for their powerful potential in terms of immersive spaces for L2 learning (Sykes, Oskoz, & Thorne, Reference Sykes, Oskoz and Thorne2008). Based on a growing body of research, these tools, including multiplayer games, virtual worlds, online collaborations, social networking, and other user-driven technologies, appear to not only support L2 acquisition, but are preferred by and perceived as beneficial by many learners (Steel & Levy, Reference Steel and Levy2013).
However, although the research in new and emerging technology is promising, there is a still a clear need for researchers to design activities and applications with sound, empirically grounded SLA principles, such as those found in TBLT. In particular, researchers may wish to draw on the criteria proposed by González-Lloret and Ortega (Reference González-Lloret, Ortega, González-Lloret and Ortega2014) when designing technology-mediated tasks or task-based courses for these constantly evolving contexts. By using these definitional features of tasks as a reference during the construction of a technology-mediated task-based curriculum, researchers may be able to gain a better understanding of how the application of a TBLT framework can best exploit the unique affordances offered by various forms of technology. Future research should consider the growing use of certain technologies, including mobile and gaming technology and social networking, as these areas are still relatively underexplored in terms of task-based research. In addition, further research exploring the use of these new technologies in a task-based framework is needed, as this will help provide us with an improved understanding of TBLT. For example, by drawing on the methodological advantages of certain technologies, researchers may be able to enhance our knowledge surrounding critical constructs like negotiation, noticing, and the role of learners’ individual differences in SLA.
Furthermore, more research is needed to investigate how the predictions of task-based frameworks, such as Robinson's cognition hypothesis or Skehan's tradeoff hypothesis, impact learners’ accuracy, complexity, and fluency in technology-mediated contexts. Research in technology-mediated TBLT demonstrates both similarities and differences in terms of task design and implementation between computer-mediated and FTF environments, suggesting that the frameworks developed for traditional oral or written task-based interactions need to be reformulated for application in new and emerging computer-mediated contexts (González-Lloret & Ortega, Reference González-Lloret, Ortega, González-Lloret and Ortega2014). Overall, as our concept of the classroom expands beyond the physical walls of a classroom, integrating mobile, web-based, and socially mediated technologies, so should our conceptualizations of tasks and the frameworks we have used to investigate them.
