471 Studies in Second Language Learning and Teaching Department of English Studies, Faculty of Pedagogy and Fine Arts, Adam Mickiewicz University, Kalisz SSLLT 8 (2). 2018. 471-495 doi: 10.14746/ssllt.2018.8.2.13 http://pressto.amu.edu.pl/index.php/ssllt Strategies in technology-enhanced language learning Yalun Zhou Rensselaer Polytechnic Institute, USA zhouy12@rpi.edu Michael Wei University of Missouri-Kansas City, USA weiyou@umkc.edu Abstract The predominant context for strategy research over the last three decades has focused on language learning situated in a conventional classroom environ- ment. Computer technology has brought about many changes in language learning and has become ecological and normalized rather than a supporting tool in the language classroom. Consequently, the landscape of language learning has been rapidly and largely changed with the normalization of tech- nologies in people’s daily communication. The pervasive use of mobile tech- nologies and easy access to online resources require that digital language learners understand and employ appropriate learning strategies for learning effectiveness and that their teachers are able and willing to teach these strat- egies as needed. This article provides an overview of the state-of-the-art re- search into technology-enhanced language learning strategies. The strategies under review include those for language learning skill areas, language subsys- tems, and self-regulated learning. At the end, we discuss the pressing issues that Digital Age language learning has posed to learners, teachers, and re- searchers and propose considerations for strategy research in digital realms. Keywords: language learning strategies; self-regulated language learning; strat- egy instruction; strategy assessment; technology enhanced language learning Yalun Zhou, Michael Wei 472 1. Introduction Consciously or at least partially consciously, almost all language learners use tools, take actions, or self-regulate their behaviors to make their language learning or lan- guage use more effective or more efficient (Cohen, 2011; O’Malley & Chamot, 1990; Oxford, 1990). Oxford’s (1990) landmark book on language learning strategies (LLS) and O’Malley and Chamot’s (1990) volume on LLS in the cognitive information-pro- cessing model fostered strategy assessment and strategy instruction, leading to up- dated theorizations in recent years (e.g., Cohen, 2011, 2018; Griffiths & Oxford, 2014; Oxford, 2011, 2017). However, the rapid technological changes of the 21st century (e.g., computer-assisted language learning, data-driven technology, online and blended learning approaches, and emerging technologies such as online games, virtual and augmented reality, immersive classroom, and telepresence) are changing the landscape of second and foreign language (L2) teaching and learning. Knowledge and practices of LLS are still essential for successful learning, even in the Digital Age, and strategies relevant to various digital learning challenges do exist (Oxford & Schramm, 2007). Yet we do not fully know how learners and/or teachers can opti- mally understand and harness strategies in technology-enhanced, innovative lan- guage learning (Becker, Rodriguez, Estrada, & Davis, 2016). Therefore, this article offers an overview of existing research on technology- enhanced LLS, following Oxford’s (2017) categorization of L2 learning strategies. The sixty-six research reviewed explore language learning strategies, including stra- tegic self-regulation, in technology-enhanced language learning (TELL) contexts. We define TELL broadly as any language learning activity that uses technological means and/or tools for efficiency, motivation, and learning style flexibility. Oxford’s cate- gorization divides L2 learning strategies into a set of interlocking but flexible sys- tems: (1) strategies for language skills area (i.e., reading, writing, listening, speaking, and related aspects) and (2) strategies for language subsystems (e.g., vocabulary and grammar). The strategies under review are arranged in a similar way. We first review strategies for L2 skills learning, then look at strategies for language subsys- tems, and finally we focus on self-regulated L2 learning. The article concludes with overarching issues in the field of language learning strategies in digital environ- ments, provides recommendations that guide language instruction in technology- enhanced contexts, and highlights questions that still need to be answered (e.g., lack of research) regarding the role of technology in the application of LLS. 2. Strategies for language learning skill areas in TELL LLS research in technology-enhanced contests are abundant in three language learning skill areas: listening, reading, and writing. It, however, is scant in speaking. Strategies in technology-enhanced language learning 473 Literature reviewed here illustrate the richness and/or scarcity of LLS research of listening, speaking, reading, and writing in the context of TELL. 2.1. Listening Utilizing the Strategy of Inventory for Language Learning (SILL) (Oxford, 1990) to evaluate students’ self-dictation activities with YouTube videos, Chang and Chang (2014) examined forty-eight Taiwanese college students’ English listening comprehension strategies on YouTube’s caption manager platform. SILL’s meta- cognitive items assess the use of strategies such as planning, setting goals, or- ganizing, noticing, paying attention, looking for opportunities to make learning effective, monitoring, and evaluating. In an Advertising English college course, Chang and Chang first spent 8 weeks presenting and having students practice top-down strategies (listening for main ideas, prediction, and drawing infer- ences) and bottom-up strategies (vocabulary, sound patterns, and syntactic pat- ters), then spent another 8 weeks implementing metacognitive strategies. In the second stage, students were required to recall and reflect upon (e.g., what I know, what I want to know, and what I learned) their metacognitive strategy development by answering questions related to: (1) strategies they used to un- derstand the online video, and (2) reasons why they could not answer certain lis- tening comprehension items and the problems they encountered. The results in- dicated that, after strategy instruction, students consciously incorporated meta- cognitive listening strategies (e.g., “I notice my English mistakes and use this in- formation to help me do better”; “I pay attention by listening when someone is speaking English in the advertisement videos”) to manage and adjust their English learning when listening YouTube videos. Students who reported using the meta- cognitive strategies in the SILL performed significantly better on listening compre- hension tests. They reinforced their listening comprehension by creating dictation questions, recalling strategy uses, and reflecting on their listening problems. Using the Metacognitive Awareness Listening Questionnaire to investigate metacognitive listening strategies awareness and podcast-use readiness of 141 Tehran college students, Rahimi and Katal (2012) found the importance of meta- cognitive listening strategies in technology-based learning environments. Strate- gies such as problem solving, planning-evaluation, directed attention, person knowledge, mental translation, and problem solving are important indicators in effectively using English podcasts. The researchers discovered that metacognitive listening strategy awareness predicts the readiness of using podcast in English lan- guage learning. Similarly, in a dissertation study investigating 27 adult Taiwanese English language learners’ strategy in comprehending authentic short documen- tary-style news videos, Slimon (2012) found that learners with higher listening Yalun Zhou, Michael Wei 474 proficiency used significantly more bottom-up (e.g., comprehension of phonemes and single words to build up meaning) and total strategies as well as recalling sig- nificantly more audio contents than those who used fewer strategies. 2.2. Reading Reading strategies in the TELL context are mainly scaffolded by platform design or software programming. For example, Dalton, Proctor, Uccelli, Mo, and Snow (2011) developed a web-based reading prototype to improve reading achievement. The goal of scaffolding is reading digital texts with embedded prompts that ask stu- dents to apply reading strategies. The six strategies that pop up for students to consider are: predict, question, clarify, summarize, visualize, and feeling. Student participants were75 monolingual English and 31 bilingual fifth-grade students in Boston area where the majority non-white student population was composed of Latinos. After the teacher introduced reading strategies offline, the students were assigned to one of the three conditions aimed at improving comprehension online (ICON) conditions of eight English folktales: reading comprehension strategies, vo- cabulary, or combined version of comprehension strategies and vocabulary. During the research, the students read eight multimedia folktales and informational texts within their respective ICON condition and completed embedded activities. The reading-comprehension instructional actions they utilized in their prototype de- sign were: (1) support strategic learning through prompted reading comprehen- sion strategies, text-specific and generic comprehension strategy hints, models, and think-alouds, (2) provide access to contents through multiple means of repre- sentation (e.g., bilingual pedagogical avatar, synchronized, real-time highlighted bi- lingual texts or vocabulary translation on screen), and (3) support affective learning through age-appropriate and appealing folktales with quality interface and leveled coaching and support. By design, all three conditions shared common set of fea- tures such as Spanish-English bilingual hints, Spanish translation of instructional supports, and text-to-speech read-aloud functionality in English and Spanish. As a result, the researchers found that the strategy and vocabulary combination group and vocabulary group outperformed the strategy alone group. One distinctive technology feature of reading online is the interactivity be- tween learners and texts. In their interactive English Language Learning System (i- ELLS), Nor, Hamat, Azman, Noor, and Bakar (2011) employed interactive tools such as Annotation and My notes to teach English reading comprehension to 81 Malay- sian college students. By design, the system embedded reading strategies that stu- dents would not be aware of, thus encouraging them to comprehend. The embed- ded tool, My notes, encouraged students to reflect on what they read and to share with peers or to comment on peers’ notes, write down questions and notes, get Strategies in technology-enhanced language learning 475 notes organized, and list unknown words. The Annotation tool allowed students to process the reading materials by applying reading strategies such as highlighting im- portant points or points that they do not understand and by writing comments into the texts. The Annotation tool provided the opportunity for students to process and internalize the text at their own pace, leading to development of reflective learning. Regarding online reading strategies, Ramli, Darus, and Bakar (2011) found in their study carried out in a Malaysian university that 92 ESL (English as second language) adult learners preferred metacognitive strategies over taking notes or reading aloud in online reading tasks. Metacognitive strategies include advanced planning and comprehension monitoring, such as global reading strategies (e.g., having a purpose in mind when reading online, checking understanding, deciding what to read closely and what to ignore), problem-solving strategies (e.g., trying to visualize information), and support strategies (e.g., seeking tools to aid com- prehension). Similarly, Roy and Crabbe’s study (2014) with 75 graduate-level, ad- vanced English learners in a Japanese technical university found that the students employed global strategies (e.g., “I have a purpose in mind when reading”) through both online and offline resources to aid their online reading. The re- searchers recommended that online reading materials developers design struc- tured and compartmentalized questions for broad design queries to make think- ing easier and channelized. In a study with seven graduate students from China, South Korea, and Taiwan at a US university in the Midwest, Park, Yang, and Hsieh (2014) utilized pre-reading think aloud before reading online texts to elicit partic- ipants’ prior knowledge about the reading passages. They found that prior knowledge in students’ native language and disciplinary background (e.g., busi- ness, chemistry, biology, health science, and instructional systems technology) as- sists their online reading comprehension. As more matured students with higher level of proficiency, the graduate students demonstrated self-regulated reading strategies such as planning, predicting, monitoring, and evaluating. On the basis of their technology-assisted research involving 137 sixth-grade learners of English in Western Cape South Africa, Klapwijk and Toit (2009) sug- gested enhancing reading comprehension strategy instruction through a blended approach. The instructional approach was composed of an interactive, multime- dia lesson on CD-ROM, an online assessment version of the comprehension test, and a booklet to guide the learners through the lesson steps. The interactive mul- timedia lesson included basic sound, a short video clip and interactive exercises that addressed three reading strategies: activating prior knowledge, summariza- tion, and lookback. According to the researchers, technological advantages such as immediate feedback, self-paced learning, and exposures to a variety of media (audio and video), on the one hand, relieved teacher’s workload, and on the other hand, motivated students to read. Yalun Zhou, Michael Wei 476 2.3. Writing When four Korean college students performed error correction in writing with the help of a free online corpus, Lextutor, Yoon and Jo (2014) found that students utilized four categories of learning strategies: metacognitive (e.g., self-evaluation/monitor- ing), cognitive (e.g., making use of materials, association, grouping, and translation), affective (e.g., lowering anxiety and self-encouragement), and social (e.g., question- ing for clarification). Among these, the category of cognitive strategies was used the most and significantly more often than the other three categories. In a German/English tandem project of Open University, UK, Stickler and Lewis (2008) paired 25 English speaking German language students in a higher intermediate German course with native German speaker partners in an adult ed- ucation institution in German. Their intention was to investigate students’ collab- orative language learning strategies in an email tandem exchange. They identified six online-specific strategies and seven tandem-specific strategies used by the lan- guage learners. The online strategies were: (1) copying the previous message to highlight mistakes or offer corrections, (2) using greetings and social niceties of email writing conventions, (3) planning for the next email by announcing the time, date, or content of next message, (4) signposting in the email to demonstrate that next part will contain correction or switch of language, (5) using symbols (high- light, underline, color-in words) for corrections, and (6) using attachments with a reminder in body of email. The seven tandem-specific strategies were: (1) offering or giving corrections, (2) evaluating partner’s performance, (3) encouraging part- ner with positive feedback, (4) offering a fair deal exchange, (5) answering explicit questions by directly responding to partner’s previous emails or referring directly back to partner’s statements, (6) planning face-to-face meeting via email to nego- tiate time and place to meet, and (7) negotiating for error corrections. According to the authors, memory strategies and compensation originally listed in Oxford’s (1990) strategy groups were either not found or were very rare in tandem collab- orative learning strategies. With the purpose of examining the role of mobile phone technology in language learning strategies, Bekleyen and Hayta (2015) conducted a study with 75 English language teaching majors in a state university in Turkey. They found that the participants used cognitive, memory, compensation, metacognitive, af- fective, and social strategies with affective strategies being the most frequently employed. Social strategies were the least common. In a bilateral tandem MOO (multiuser domain, objected-oriented) project be- tween Irish (N = 29) and German (N = 22) college students, Schwienbhorst (2002) in- vestigated learners’ intended discourse repair strategies in native/nonnative speaker email exchange. Discourse repair strategies arose when there was incomplete Strategies in technology-enhanced language learning 477 understanding and students used strategies such as negotiation of meaning, com- promise overt request for clarification, self- and other- repetitions (i.e., exact or par- aphrasing), complete or partial repetition, code switching, etc. The findings indicate that active strategies or processes of meaning negotiation are prominent in repair- ing communication. In the case of misunderstandings caused by language barriers, the repair strategies the participants used the most often were asking partners to translate, paraphrase, clarify, guess, and negotiate meaning. In a Chinese university, Tang, Xie, and Wang (2011) designed a Wiki-based collaborative writing environment for their e-Commerce Specialty English course. This environment was composed of four types of tools for students to use when completing writing assignments: (1) tag web resources, an online se- mantic annotator allowing learners to conceptually model semantic relations, (2) peer revision and feedback to assist group members in coordination of col- laborative learning process, (3) semantic search that facilitated search and re- trieval options, and (4) page histories that recorded every major review version. Three learning strategies were identified by the researchers, namely, collabora- tion and knowledge sharing, peer assessment, and monitoring the stages of the writing process. Evaluation results showed that Wiki-based collaborative writing can promote student engagement, group work, and audience awareness. 2.4. Speaking Surprisingly, speaking strategies research in the TELL context is scant. This might be because of the constraints of technology available for interactive speaking and also speech recognition technologies. Taking advantage of video feedback, Hung (2016) conducted a project over the duration of a semester among 60 EFL learners in Taiwan. The project required students to post a 3-minute video presentation on Facebook for questions and discussions occurred in class, then two 2-minutes video-mediated oral feedback. The researcher investigated learners’ strategic behaviors in the process of developing video-mediated peer feedback and explored the strategies employed by learners when giving video- mediated oral feedback. Hung’s findings revealed that the most frequently used strategy was modifying language for accuracy and constant practices, along with watching others’ oral comments, jotting down comments for future improve- ments, and discussing with classmates. 3. Strategies for language learning subsystems in TELL Oxford (2011) categorizes LLS use into main areas such as the four language learning skill in learning the target language systems and subsystems (grammar Yalun Zhou, Michael Wei 478 and vocabulary). Research focusing on LLS use with respect to the remaining L2 sub- areas in the TELL context (e.g., affective and pragmatics) could not be found in major linguistics databases. We, therefore, focus our review on vocabulary and grammar. 3.1. Vocabulary Vocabulary learning strategies might be the most productive research area in TELL, though grammar learning strategies sometimes accompany vocabulary learning strat- egies. Li (2009) compared vocabulary learning strategies with or without technology support among Chinese speaking ESL students in Canada. 24 high school students were asked to read 10 short Aesop’s fables, among which, five in paper format and five in e-Lective platform. The e-Lective features English-English and English-Chinese word definition, an unknown word bank for students to record what they have looked up, a partial and blank word bank for cloze test and comprehension exercise, and a grammar notebook for students to look up parts of speech when inferring meanings of words. The strategies used in the e-Lective condition included using online diction- aries, taking notes, guessing and inferring, summarizing and making connections, reading aloud, and discussing. According to the participants, compared to those in printed texts, e-Lective allowed them to utilize more strategies in ways summarized in Table 1. Li pointed out from the results that technology-enhanced scaffolding can ef- fectively assist students in advancing their learning strategies, potentially optimizing their reading-based vocabulary acquisition. Overall, students in the e-Lective condition used higher levels of cognitive and social strategies (e.g., summarizing and discussing), whereas the in paper condition they employed fewer social strategies (e.g., consulting with the researcher and peers regarding meanings of words). Table 1 Strategies used with e-Lective and associated reading activities (Li, 2009, pp. 131-133) Strategies used with e-Lective Associated reading strategies Note taking Taking more, well-organized notes with e-Lective to facilitate memorization and review Guessing and inferring Using contextual cue-oriented guessing strategies with higher accuracy than in the paper condition Summarizing and making connections Engaging in the use of higher levels of cognitive strategies that promoted deeper semantic processing and better vocabulary retention, such as summarizing, applying, and manipu- lating phrases and words Reading aloud Being able to use the built-in text-to-speech module to read aloud and practice the pronun- ciation in words, sentences, and whole texts; attention paid to syllables and stress patterns Discussing Using a wide range of cognitive strategies to process the reading and retain vocabulary (e.g., repeating, quoting, referencing the texts); switching languages to make communica- tion as comprehensive as possible; translating to verify understanding; and reasoning – a higher level of semantic processing of information Strategies in technology-enhanced language learning 479 Furthermore, gamification of learning so frequent in TELL makes it natural to learn vocabulary via computer games. Smith, Li, Drobisz, Park, & Kim (2013) designed a vocabulary learning game for intermediate level Chinese students enrolled in a College English course. Fifty-seven students used the interference- based computer games the researcher designed to learn new vocabulary words and make inferences about a text. The interactive game-like interface forced learners to create sentences through constrained choices. Smith et al.’s (2013) experimental study found that inference-based computer games enable stu- dents to process the vocabulary more deeply and have better recall. The strate- gies that the students needed to incorporate with the game-like constrained sentence-writing were making inferences, encoding more effectively, comparing the game to reading lists of words, and answering multiple-choice questions. Gallo-Crail and Zerwekh (2002) researched how L2 learners used different strategies with different web-based tools as they studied new vocabulary and how this affected their success in learning and mastering such vocabulary. The participants in this study were 25 beginning level students of Tagalog at North- ern Illinois University. The researchers identified five types of learning strategies supporting online vocabulary learning: memory strategy (e.g., association), cog- nitive strategy (e.g., translation), compensation (e.g., use of linguistic and other clues), affective (e.g., developing cultural understanding), and metacognitive (e.g., overview and lining with previous learning materials). The more diverse strategies students used to learn vocabulary, they performed in vocabulary tests. Some researchers and instructional technologists design and investigate vocabulary learning strategy software or applications. For instance, Lan (2013) developed a co-sharing-based strategy learning system, Mywordtools, for 61 sixth-grade students in Taipei to learn English vocabulary. This application ena- bles students to learn vocabulary by using the available language learning strat- egies embedded in the design. When an L2 word is chosen, the learner can look up the strategies that have been used by all of the other learners in Mywordtools or select one of the strategies that he or she wants to use to aid the process of learning and memorize the word. The choices are: note-taking, contextualiza- tion, grouping, imagery, recombination, deduction, analysis, translation, etc. The users have four options (i.e., audio, video, image, and note) to record their learning strategies. Once the learners have uploaded their learning strategies, the learning module allows them to look up the strategies used by other peers. The function of embedded strategies sharing is to raise the awareness of learners so that they can self-evaluate their own strategies, make them cognizant of gaps in their knowledge, and enable them to re-construct their strategies or increase their self-confidence. The results of this study indicated that students using Mywordtools to practice and share vocabulary learning strategies outperformed Yalun Zhou, Michael Wei 480 both those who did not use Mywordtools and those who used the platform but without sharing. It was also found that strategy sharing helped L2 learners use more vocabulary learning strategies, and they consequently performed signifi- cantly better than those who did not engage in strategy sharing. Ou Yang and Wu (2015) incorporated LLS instruction into their e-learning platform called MyEVA. MyEVA is a mixed-modality English vocabulary learning strategies system. In this system, they used Schmitt’s (1997) division of strate- gies for learning L2 vocabulary into discovery (i.e., determination strategy and social strategy) and consolidation (i.e., social strategy, memory strategy, cogni- tive/metacognitive strategy, pictures/imagery, related/unrelated words, group- ing, the word’s orthographical and phonological forms). MyEVA was piloted with nine undergraduate students in northern Taiwan. The findings indicate that the vocabulary learning mode that allows learners to pre-determine a preferred learning strategy (e.g., word-card, flashcard, Chinese-assonance, synonym, an- tonym, imagery, grouping, and clipping) before actual learning resulted in great- est vocabulary acquisition and best retention. 3.2. Grammar Research on the use of grammar strategies by learners has been scant (Cohen, Pinilla-Herrera, Thompson, & Witzig, 2011; Oxford & Lee, 2007; see the paper by Pawlak in this issue). Even more scant is technology-enhanced grammar strat- egies research. However, an exhaustive search of major databases allowed us to identify several attempts in this area. To strategize the learning and using of Spanish grammar, Cohen et al. (2011) designed a website to track grammar strategy use by 15 students of Span- ish. Unlike a collection of grammar rules, this website collected 72 strategies that were found to be effective for Spanish learners. It contained two sections. One section included strategies for a particular grammar form that students thought were necessary for them to learn. The other section contained strate- gies for enhancing learners’ use of grammar strategies. In this section, learners can select strategies that match their learning style and their ideas about what they can put into practice. To examine the accessibility and navigation of the website, a small-scale user test was administrated. The research questions were related to strategies that the learners chose, the extent to which these strategies were helpful and the rationale for choosing specific strategies. The results indi- cated that the learners thought 73% of the grammar strategies were helpful and that found certain strategies helped them improve their Spanish grammar per- formance. In addition, the students reported improvement in class activities, on tests, and on writing assignments during the 6-8 weeks of practicing with the Strategies in technology-enhanced language learning 481 grammar strategies website. Some participants even reported improvement in their ability and confidence to use grammar forms that they had struggled with before. Overall, the learners benefited from use of the grammar strategies web- site. It can thus be assumed that reliance on the strategies included in the web- site allowed them to enhance their mastery of grammar. A study that examined the effects of the application of grammar strategies that aided learning of specific grammar forms was conducted by Hwu (2007). Hwu investigated how different students used a grammar application created by the re- searcher. The objective of the application was to teach the uses of two Spanish past tense forms. He asked learners to watch Spanish soap opera clips that con- tained various pragmatic meanings of the two forms in conversations. Each of the 19 clip lessons included in the application consisted of one component that explic- itly asked the students to explain how a linguistic form was used in the clip, provide their own explanation of the form in terms of the speaker’s intention, indicate the reference point of the intention, decide whether the other word is acceptable in that context and why/why not, and to explain of the use of the target verb form in the sense of pragmatics. The grammar strategies instruction provided by means of this application was integrated into the syllabus and a pre- and posttest was ad- ministrated to determine whether the students’ understanding had improved over the semester. The results indicated that the experiment group students spent a substantial amount of time with the grammar strategies application, which re- sulted in significant improvement from pretest to posttest while the control group students remained at the same level. Furthermore, Hwu (2007) analyzed the cor- respondence of the strategy preferences expressed in the SILL (Oxford, 1990) and predominant types of learning styles. The results indicated that intuitive students tended to use cognitive strategies and developed their own understanding of how target language pragmatics works. Sensing participants, on the other hand, tended to use memory strategies to memorize grammar explanations. The only cognitive strategies sensing students used were making summaries of the grammar expla- nations and reasoning grammar explanations deductively. Another study focusing on grammar strategies in the context of TELL ex- plored the effect of using self-explanation (e.g., infer and reflect) on a web- based Chinese sentence-learning system and was conducted by Chang, Lee, Su, and Wang (2016). They integrated a self-explanation strategy into a Chinese- learning system that included self-explanation prompts, instructional feedback, and remedial learning materials. The self-explanation strategy provoked the stu- dents to discover, analyze, and overcome their misconceptions about Chinese sentences. When the students were inspired to identify and self-explain their errors, they had to infer possible reasons for the errors and to discover what they had misunderstood and if they could revise or correct their mistakes. To Yalun Zhou, Michael Wei 482 determine the effect of the use of the self-explanation grammar strategy web- based application, the researchers had the students complete pre- and post- tests, and sentence-structuring exercises. After comparing grammar test scores and cognitive loads of the experiment group and control group, the researchers found greater learning outcomes in the experimental group in terms of grammar and sentence structure, as indicated by the higher means on the posttest. Three rounds of comparisons for sentence-structuring exercises between the experi- ment and control groups indicated that, when in the first round, the numbers of errors made by the experiment and control groups were 67 vs. 86; the results in the second and third round were 29 vs. 49 and 11 vs. 27, respectively. There were, however, no significant differences between the experiment group and control group in terms of the cognitive loads involved in the performance of the grammar tasks. Although the self-explanation strategy was effective in learning Chinese grammar, the students complained that the process was time consum- ing and did not always enable them to eliminate their errors. 4. Strategic, self-regulated language learning with technology Despite different purposes of using strategies to learn the language skills and subsystems of the target language, self-regulation is crucial in the success of lan- guage learning. Self-regulation is a process in which people organize and man- age their learning, including control of their time, thoughts, emotions, behav- iors, and environment (cf. Zimmerman, 1998). The richness of the technology design and applications available causes teachers to consider integrating tech- nology in and out of language classrooms and makes self-regulated learning strategies a necessary skill set for L2 learners. It should be noted that all learning strategies are aimed at self-regulation, although self-regulation as a specific con- struct was not linked to language learning strategies until the late twentieth cen- tury (see Oxford, 1999).1 If learners are motivated, they autonomously select a particular activity, decide how long they are willing to persist in it, and what effort they are going to invest (Dörnyei, 2001). In understanding the importance of self-regulated learning strategies for L2 proficiency, Oxford (2011) distin- guishes three dimensions of strategic self-regulation. The three dimensions are: 1) cognitive strategies for remembering and processing language and met- acognitive strategies for planning, organizing, monitoring, and evaluat- ing in the cognitive area; 1 Autonomy was first associated with language learning strategies several decades before that (Oxford, 1999). Strategies in technology-enhanced language learning 483 2) affective strategies linked with emotions, beliefs, attitudes, and motiva- tion and meta-affective strategies for planning, organizing, monitoring, and evaluating in the affective area; 3) sociocultural-interactive strategies for contexts, communication, and culture and meta-social strategies for planning, organizing, monitoring, and evaluating in the sociocultural-interactive area. This section will follow Oxford’s three dimensions to look into research findings of strategic, self-regulated language learning enhanced with technologies. 4.1. Cognitive/metacognitive dimension Self-regulated learning strategies are crucially important in online learning envi- ronments. Chung’s (2015) questionnaires administered to 441 Taiwanese col- lege students taking a Massive Open Online Course (MOOC) revealed that high- level English learners utilize more self-regulated strategies in the process of learning, such as cognitive regulation strategies (e.g., rehearsal, elaboration, or- ganization, critical thinking, comprehension, and correction), motivational reg- ulation strategies (e.g., intrinsic, task value, success expectation, and positive affectivity), and resource management strategies (e.g., environment, adjust- ment, peer cooperation, and seeking assistance). In technology-enhanced language learning classes, researchers found it is effective to include self-regulation strategies in task design. For instance, in an Australian university, An (2013) integrated self-regulated tasks into a Chinese language course built around the web-based podcasting platform, ChinesePod. In her design, pre-tasks exposed the 49 student participants to extensive au- thentic Chinese language use in context through online podcasts. This involved the students’ self-study of the podcast lessons, which included listening to the podcasts and understanding the contents. The major tasks involved students’ creating, writing, re-writing their own dialogues and plays. The report stage was when students acted out their self-created plays or videos in class and received feedback. An (2013) reported that the task design, where self-regulation strate- gies were embedded, yielded impressive learning outcomes in terms of vocab- ulary, grammar, and improvement from first to final writing drafts. In another study exploring the effects of a self-monitoring strategy on stu- dents’ academic performance and motivational beliefs in web-based instruc- tion, Chang (2007) found that the strategy had a significant effect on students in these areas. The instructor required the 99 students in Freshman English class to keep a self-monitoring recording form each time they logged into the course site. The form functioned as a record and an alert of time logs, learning modules, Yalun Zhou, Michael Wei 484 prediction and real test scores. Students who employed self-monitoring strategies outperformed students who did not on both academic performance and moti- vational beliefs. Within the higher-level English proficiency group, students who employed the self-monitoring strategy obtained higher scores than those who did not. Chang’s research revealed that self-monitoring treatment in instruc- tional design compensated for the lack of use of metacognitive strategies among the lower-level English proficiency group. Self-instruction, self-regulation, and learning autonomy are crucial for dis- tance language learners. In a study involving 37 students learning French (N = 19, of which 4 were in classroom mode) and Japanese (N = 18, of which 5 were classroom mode), White (1995) found that distance learners used strategies more often than classroom learners (e.g., 26.6 instances vs. 10.2 of strategy use in self-reports). With respect to metacognitive strategies, distance learners made greater use of the monitoring and evaluation dimensions of metacogni- tion than did classroom learners. Distance language learners therefore need to develop an understanding of the nature of language learning as well as an ap- propriate repertoire of language learning strategies. Among the three strategies that distance learners use, the most influential self-regulation strategy is self- management as it fosters learner autonomy. It is important that teachers facilitate or assist the development of learners’ self-regulated strategies in strategic language learning in TELL environments. Hou- rigan and Murray (2010) pointed out the importance of developing learning strat- egies in digital times because students of the 21st century are not necessarily “dig- ital natives” (p. 212). Similarly, it is necessary to provide opportunities for learners to develop metacognitive awareness and to guide them in improving and expand- ing their knowledge about learning and becoming autonomous language learners (Hauck, 2005). Without adequate training or guidance, technology-based lan- guage learning outcomes may not be ideal, for instance, for effective English lis- tening learning (Zhang & Song, 2009). One good example of strategy instruction is what Saks and Leijen (2015) did in an attempt to find a more efficient way to support learners’ use of cognitive and metacognitive learning strategies. They in- tegrated strategy learning as scaffolding with strategy prompts to improve stu- dents’ learning efficiency at various phrases of learning. In their blended Tourism English course, 28 Estonian students were encouraged to plan, monitor, and self- evaluate their learning activities with the help of learning journals. The evaluation of the course indicated that the most obvious improvement resulting from such scaffolded strategy prompts in course design are active use of language as well as compensation, and social strategies. Assignments prompting learners’ use of cog- nitive and metacognitive LLS facilitate the development of content knowledge and language skills, and also support self-expression in English. Strategies in technology-enhanced language learning 485 Similarly, in Spain, Pujola (2002) designed a web-based program called Im- PRESSions, consisting of multimedia news (newspaper, radio, and television) to facilitate the use of reading and listening comprehension strategies in the course of self-study. It was designed in response to Garrett’s (1995) assumption that stu- dents lack awareness or strategies for help seeking. The design contained four modules: newspaper, radio, television, and expert (note: this module was de- signed to provide grammar practices for the learners). 22 adult English learners reported that inferring strategies in context was what they used the most in this program. The participants also engaged in analysis of parts of the words, similari- ties between the target language with their native language, and links to previous news item. Examples of prompts that facilitated participants’ thinking about help seeking and learning strategies in the form of a pop-up button ASK-THE-EXPERTS included: What can I do when I do not know a word? What can I guess the mean- ing of a word? When can I use skimming? How can I improve my reading? What can I do when I cannot follow the speed of the speaker? What can I do when I hear too much unfamiliar information? (Pujola, 2002, p. 256). The most frequently consulted listening strategies question was what can be done when students can- not follow the speaker, whereas the most frequently consulted reading strategies question was when they can use skimming and scanning. 4.2. Affective/meta-affective dimension Technology-enhanced self-regulated L2 learning is related to positive affective learning outcomes and language gains (Lai, Wang, Li, & Hu, 2016). Affective strat- egies are linked with emotions, beliefs, attitudes, and motivation, as well as soci- ocultural-interactive strategies for contexts, communication, and culture (Oxford, 2011). Self-regulatory strategies are influential in promoting motivation and au- tonomous learning (Kormos & Csizér, 2014). Kondo, Ishikawa, Smith, Sakamoto, Shimomura, & Wada (2012) designed a MALL (mobile assisted language learning) self-regulated learning module to help improve students’ scores on the TOEIC listening and reading tests. Their goal was to investigate whether certain MALL practices can foster an advanced form of self-study and self-regulated learning. Their module was composed of five-steps in order to foster, in the initial stage of self-study, and in the long run, to support students’ gradual transition to self-regulated learning. 88 first-year students at Kyoto University, Japan, participated in this study. In this strategic language learning pedagogical design, students took responsibility for stimulat- ing and sustaining their motivation so that they could formulate, carry out, and evaluate strategic learning plans. Results indicated that students in the MALL group improved self-study behaviors and spent more time on studying outside Yalun Zhou, Michael Wei 486 of class. They increased their scores in both the listening and reading sections (e.g., an increase of 40.83 in the MALL group vs. 18.15 in the control group). Lai and Gu’s (2011) survey study with 279 Hong Kong college students learning foreign languages (i.e., Chinese, English, French, Japanese, Spanish, and Korean) investigated how technology enhanced students’ self-regulated language learning outside the classroom. Data analyses indicated that students’ motiva- tions for using technology in self-regulated L2 learning included: regulating emo- tions and making learning appealing, planning, evaluating, and monitoring learn- ing progress, enhancing social connections and seeking help, making commit- ment to learning goals, making use of learning resources, and having better cul- tural understanding. In addition, teachers were found to provide important emo- tional support in students’ self-directed language learning with technologies out- side of classroom. The strategies that students thought were effective in support- ing self-regulated language learning with technology included encouraging stu- dents to use technological resources and using technology in class (Lai, 2015). 4.3. Sociocultural-interactive/meta-social dimension Informed strategy use is particularly important in the context of online language learning, where learner interaction often takes place in environments that stu- dents are either less familiar with or more interested in communication with their peers rather than in educational purposes. In an internet-mediated inter- cultural foreign language exchange project, Hauck and Hampel (2008) created a telecollaborative exchange with students from three different countries, France (N = 10 learning English), the UK (N = 5 learning French), and United States (N = 10 learning French). Telecollaboration takes place when learners in internation- ally parallel language classes use internet communication tools such as email, synchronous chat, threaded discussion and so on to support sociocultural inter- action. In Hauck and Hampel’s project, the participants spent 10 weeks taking part in a structured exchange exploring the benefits of synchronous and asyn- chronous learning environments for partnership language learning. The analysis of the online interactions yielded the most examples of affective strategies (e.g., lowering anxiety, encouraging, and taking emotional temperature) and social strategies (e.g., asking questions, empathizing with others, getting to know oth- ers, and facilitating interaction) proposed by Oxford (1990). In addition, a new set of strategies, which the researchers termed socio-environmental strategies played a vital role in successful online learning of languages and cultures. The researchers claimed that interactions in online environments require different ways of making and maintaining contact, finding out about common interests, and developing an identify as a group. Compared to face-to-face communication, Strategies in technology-enhanced language learning 487 affective and social skills cannot simply be transferred but need to tailored to virtual learning environments. Due to the nature of online intercultural ex- changes, strategy (especially metacognitive strategy) instruction, is an im- portant step in facilitating language learning. The online language learners need continuous support from teachers in terms of LLS use. 5. Discussion The arrival of the Digital Age has been a white water change, a metaphor de- scribing the rapid, complex and all-encompassing nature of this technological wave (Oxford 2008, p. 191, cited in Oxford & Lin, 2011). The widespread availa- bility of technology tools brought about new opportunities and challenges in language learning strategy pedagogical design and research, and, consequently, new considerations for instructed second language acquisition. As Chapelle (2009) writes, “Technology dramatically extends and changes the breadth and depth of exposure that learners can have with the target language and interactive events in which they have the opportunity for language focus” (p. 750). The in- creased use of technology in language classrooms makes it no longer appropriate to think of it as a supporting tool in face-to-face language classroom (Nunan, 2000). Technology is far more than this. Learners are now challenged to explore strategies for effective language learning in digital realms (Oxford & Lin, 2011). This new context of language learning calls for new pedagogical designs involving strategy instruction and new methodologies for research into LLS. The overview undertaken in this article revealed that although 21st cen- tury L2 learners, especially those in technologically developed countries, are digital natives (Hourigan & Murray, 2010), they are not necessarily experts in learning with technologies. This is especially true in the case of language learn- ing. Although a large portion of language learning extends to outside of the classroom due to the pervasive employment of multimodal technologies, learn- ers might not be self-regulating or autonomous unless they have been explicitly taught to use learning strategies. Digital Age learners who benefit from proper language learning strategy instruction outperform their counterparts who have not received such training both in language learning efficiency and language skills. Strategies-based instruction which is enhanced by technology produces impressive outcomes in terms of developing strategic, self-regulated language learners in the Digital Age (Mutlu & Eroz-Tuga, 2013). We strongly agree with Salaberry’s (2001) proposal that the most im- portant challenge posed by TELL is the identification of pedagogical objectives that technology-based teaching is to achieve. The diversity and universality of modern technologies available have challenged both language teachers and Yalun Zhou, Michael Wei 488 learners. The teacher’s role is crucial in identifying the best technology tools and guiding students to be strategic, self-regulated language learners when using technologies. A teacher without ample knowledge and skill in evaluating and utilizing effective technological tools may not be a good teacher in the Digital Age. Kern (2006) examined how the rapidly changing communication landscape of the 21st century affects the way we learn, use, and teach languages. While technological devices and easy access to them are powerfully transforming how human society communicates, researchers are becoming increasingly aware of the importance of strategy use with technology in the cognitive and affective di- mensions of strategic, self-regulated learning. In contrast, research into the use of grammar strategies as well as the sociocultural-interactive dimension of strategic, self-regulated learning seems much less fertile, despite the availability of authen- tic, interactive materials online and on mobile apps. It is important for 21st cen- tury language teachers to have “new understandings of language and communi- cation, critical awareness of the relationships among technology, language, cul- ture, and society, and new trends in research methods” (Kern, 2006, p. 183). Alt- hough communication strategies were originally categorized by Oxford (1990) as “tools for active, self-directed involvement” (p. 1) for the development of com- municative competence, at this point in history they are also crucial strategies in computer-mediated contexts and may be considered very important in pedagog- ical designs and research informing synchronous, virtual communication. 6. Conclusion and recommendations In this paper, we reviewed existing research on language learning strategies in TELL environments, first in relation to specific language skills (i.e., listening, speak- ing, reading, and writing), then as associated with target language subsystems, such as vocabulary and grammar, and finally, as linked to strategic, self-regulated language learning. The technology-enhanced language learning strategies re- viewed demonstrate the specifics of what learners and teachers do with technol- ogies in the Digital Age, how they embed language learning strategies into games, online platforms, and/or apps, and how they cultivate self-strategically self-regu- lated learning. If the communicative approach has profoundly changed the com- ponents of language classroom, the rapid technological changes and pervasive presence of interactive Web 2.0 tools (e.g., voice interactive CALL, Kern & War- schauer, 2000) in the 21st century have extended language teaching and learning to any time, at any place, with any device. New thoughts, practices, and research pro- tocols are needed to cope with the rapidly growing new technologies (e.g., smart phones, tablets, 3D glasses, real-time virtual interactive tools) and new learn- ing environments (e.g., virtual reality, mixed reality, and immersive, intelligent Strategies in technology-enhanced language learning 489 learning environment). Although the unprecedented human-computer interac- tion formats (e.g., emails, Facebook, Google hangout, Skype, Twitter, WeChat, QQ) have provided more authentic language learning venues, it does not nec- essarily mean that our learners of the 21st century are born to know how to learn a foreign language effectively with these technologies and how to self- regulate their learning outside the classroom. Instead, there is a need to equip learners with strategies for effective human-computer and sociocultural inter- action. We therefore make the following recommendations in terms of language learning strategy theory and practice for more effective language learning. First, with the embeddedness of technology in and out of language class- rooms, in addition to traditional research protocols, we call for more research in- struments to investigate technology-enhanced LLS (see e.g., Chai, Wong, & King, 2016 on learning strategies and strategy instruction in TELL contexts). Strategies which were not included in traditional frameworks of LLS need to be added, such as, for instance, socio-environmental strategies, proposed by Hauck and Hampel (2008), and human-computer interaction strategies with emerging technologies. In addition, social language leaning strategies, which were seemingly less im- portant in traditional schemes, are now known as collaborative language learning strategies and identified as one of the most important strategy sets in email tan- dem exchange tasks (Stickler & Lewis, 2008). Furthermore, normalization of tech- nology in language classrooms and the multi-faceted aspects of language learning technologies have altered traditional language learning and teaching approaches. This change calls for new learning strategies, digitalized data collection, and data analysis. It also presents new challenges for research design and instrument-build- ing and requires a new frontier of research methodologies (Stickler & Shi, 2016) in language learning strategies and self-regulated learning with TELL. Second, due to specific and ungeneralizable technological infrastructures, most TELL-based strategy research has investigated the effectiveness of a technol- ogy and/or platform in a laboratory setting, often including only short-term treat- ments. Instruction in language learning strategies and self-regulated learning with TELL over longer periods of time (e.g., a semester), taking place in intact classes (e.g., Zhou, 2016) seems to be more suitable in digital realms. More research is needed to explore how 21st century L2 teachers and learners handle strategies and self-regulated learning in technology normalized day-to-day classroom operations. Third, language learners are challenged by new forms of learning and seek new strategies for learning (Oxford & Lin, 2011). In addition, the availability of new technologies and language learning tools has grown much faster than the preparation of language teachers. Learning strategy instruction should be inte- grated into the curriculum of technology-enhanced language learning. Successful use of new language learning technology tools and new types of learning strategies Yalun Zhou, Michael Wei 490 depends on language teachers’ increased knowledge and dedication to help their students gain awareness of and skill in using optimal LLS. This calls for a change in the curricula for language teacher education. In addition to knowing about teaching methodologies and assessments of language learning in traditional ways, language teachers in digital realms also need to be equipped with knowledge and skills to: (1) identify technical attributes specific to the new technologies that can be feasibly integrated into and engaged with classroom instruction, and (2) design technology- enhanced pedagogy with LLS orientation for their students. Finally, emerging technologies (e.g., Web 2.0, augmented reality, Google glasses) and learning environments (virtual reality, 3D, mixed reality, cognitive immersive), which have been designed in collaboration with artists, program- mers, and language educators, have opened up a new era for L2 learning re- search, including strategy research. There are many unknowns in this new form of research. Investigations into language learning strategies and the effective- ness of strategies-based instruction need to be expanded and diversified taking into account new types of human-computer interactions and modes of learning. In conclusion, technology has changed considerably since the incorpora- tion of computers into language learning and teaching in the 1980s. It has shifted from being a tutorial tool to an ecological tool integral to language learn- ing and language teaching. It has transformed from being a concept to a reality. New initiatives have begun to update theory, practices, and research in com- puter-assisted learning (Bush, 2008; Garrett, 2009). As for the field of language learning strategies, technology has offered, and continues to offer, research findings and practical insights concerning strategies that make L2 learning more effective (cf. Griffiths & Oxford, 2014). Rapidly growing new technologies and emerging, immersive learning environments call for a quick reaction from the- ory, research and practice of language learning strategies. It is time for research- ers and practitioners to rethink the role of TELL and immersive, interactive, learning environments that require reliance on language learning strategies. Language learning strategies have to be reconsidered (Bekleyen & Hayta, 2015) since they must be adapted substantively to new technological devices and learning environments. New initiatives, then, must be brought into the field of language strategy instruction, assessment, and research. Strategies in technology-enhanced language learning 491 References An, I. S. (2013). Integrating technology-enhanced student self-regulated tasks into university Chinese language course. International Journal of Com- puter-Assisted Language Learning and Teaching, 3(1), 1-15. Becker, A., Rodriguez, J. C., Estrada, V., & Davis, A. (2016). 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