Recent years have shown an explosion of interest in using computers for language teaching and learning. A decade ago, the use of computers in the language classroom was of concern only to a small number of specialists. However, with the advent of multimedia computing and the Internet, the role of computers in language instruction has now become an important issue confronting large numbers of language teachers throughout the world. This article will provide an overview of current teaching practices and research related to the uses of computers in the language classroom. It will be divided into four main parts: (1) a brief history of computerassisted language learning (CALL), (2) a survey of current practices and research, (3) a prospectus toward the 21st century, and (4) a list of resources for further information. The History of CALL Computers have been used for language teaching since the 1960s. This 30+ year history can be roughly divided into three main stages: behavioristic CALL, communicative CALL, and integrative CALL. Each stage corresponds to a certain level of technology as well as a certain pedagogical approach. Behavioristic CALL, conceived in the 1950s and implemented in the 1960s and 1970s, could be considered a sub-component of the broader field of computer-assisted instruction. Informed by the behaviorist learning model, this mode of CALL featured repetitive language drills, referred to as drill-and-practice (or, pejoratively, as "drill-and-kill"). In this paradigm, especially popular in the United States, the computer was viewed as a mechanical tutor which never grew tired or judgmental and allowed students to work at an individual pace. Though behaviorist CALL eventually gravitated to the personal computer, it was first designed and implemented in the era of the mainframe. The best-known tutorial system, PLATO, ran on its own special hardware consisting of a central computer and terminals and featured extensive drills, grammatical explanations, and translation tests at various intervals (Ahmad, Corbett, Rogers, & Sussex, 1985). The next stage, communicative CALL, emerged in the late 1970s and early 1980s, at the same time that behavioristic approaches to language teaching were being rejected at both the theoretical and pedagogical level, and when new personal computers were creating greater possibilities for individual work. Proponents of communicative CALL stressed that computer-based activities should focus more on using forms than on the forms themselves, teach grammar implicitly rather than implicitly, allow and encourage students to generate original utterances rather than just manipulate prefabricated language, and use the target language predominantly or even exclusively (Jones & Fortescue, 1987; Phillips, 1987; Underwood, 1984). Communicative CALL corresponded to cognitive theories which stressed that learning was a process of discovery, expression, and development. Popular CALL software developed in this period included text reconstruction programs (which allowed students working alone o...

Recently interest has grown concerning the uses of online communication for language teaching. Yet this growing interest in computer-mediated collaborative language learning has not been matched by sufficient research and theory. This article introduces a conceptual framework for understanding the role of computer-mediated interaction based on a sociocultural analysis of the relationship among text, talk, and learning. The article then analyzes current research according to five features particular to online interaction. THE RAPID GROWTH OF THE INTERNET,arguably the fastest growth of any technology in history, has caught the attention of language teachers.' The number of regional and national presentations related to online language learning has expanded geometrically in recent years. Many state and national meetings and special symposia have been devoted to this theme.* Yet this growing interest in computer-mediated collaborative language learning has not yet been matched by sufficient attention to research and theory.One purpose of this article is to explore the nature of computer-mediated communication (CMC) by using a conceptual framework that starts with well-known theories of input and output and leads to sociocultural learning theory.Another purpose is to examine classroom accounts of CMC's potential for promoting collaborative language learning, with specific reference to five features that distinguish CMC from other communication media: (a) text-based and computer-mediated interaction, (b) manyto-many3 communication, (c) time-and place-independence (d) long distance exchanges, and (e) hypermedia links. In some cases these accounts constitute rigorous research studies; in 7'he Modern LanguageJournal, 81, iv, (1997) 01997 The Modern Language,Journal 0026-7902/97/470-481 $1.50/0other cases they are teachers' personal narratives. Because the entire field of CMC is so new, a broad survey of this type can help identify issues and trends that may deserve further attention and research. CONCEPTUAL FRAMEWORKPerhaps the best known perspective for looking at cooperative communication in the language classroom was originally derived from Krashen's (1985) Input Hypothesis, but it has undergone significant additions and changes. Krashen claimed that the development of a second language (L2) is almost wholly dependent on the amount of comprehensible input that one receives. Researchers have investigated the types of conversational interactions among learners that facilitate the intake of comprehensible input (for reviews, see Long, 1996;Pica, 1994). In this model, the purpose of interaction is to provide the input-or, in some views, the output (Swain, 1985)-to make L2 development possible. This framework is useful for understanding the benefits of classroom interaction, both in general and also via CMC. For example, psycholinguistic researchers have investigated the effects of strategies such as noticing input (e.g., Doughty, 1991;Schmidt, 1993;Sharwood Smith, 1993) and planning output (Crookes, 1989).However, this per...

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This study assessed the impact of flipped instruction on students' out-of-class study time, exam performance, preference, motivation, and perceptions in two sections of a large undergraduate chemistry course. Flipped instruction caused a shift in student workload without appreciably changing the overall study time. The treatment impact on student performance gradually diminished over time, showing a small but statistically significant effect with the final exam. No marked interaction was identified, indicating that flipped instruction benefited students of diverse backgrounds uniformly. Students in the flipped section showed mixed feelings with about one fifth of them displaying polarized attitudes. Open-ended student survey responses revealed non-compliance with pre-class studying as a serious implementation issue: By slowing down the overall pace of the class, it negatively affected students with different study behaviors and characteristics in ways that partly explained the small, diminishing treatment effect and absence of marked interaction.

This qualitative study compared the availability of, access to, and use of new technologies in a group of low– and high–socioeconomic status (SES) California high schools. Although student-computer ratios in the schools were similar, the social contexts of computer use differed, with low-SES schools affected by uneven human support networks, irregular home access to computers by students, and pressure to raise school test scores while addressing the needs of large numbers of English learners. These differences were expressed within three main patterns of technology access and use, labeled performativity, workability, and complexity, each of which shaped schools’ efforts to deploy new technologies for academic preparation.

This article analyzes the emergence of a new stage of global capitalism, called informationalism, and its consequences for English language teaching, focusing on three critical issues. First, globalization will result in the further spread of English as an international language and a shift of authority to nonnative speakers and dialects. This change will call into question basic notions of language, culture, context, and the relationship between ESL and EFL. Second, economic and employment trends will change the way English is used. Increasingly, nonnative speakers will need to use the language daily for presentation of complex ideas, international collaboration and negotiation, and location and critical interpretation of rapidly changing information. Finally, new information technologies will transform notions of literacy, making online navigation and research, interpretation and authoring of hypermedia, and synchronous and asynchronous on-line communication critical skills for learners of English. The above changes, taken together, will render ineffective curricula based strictly on syntactic or functional elements or narrowly defined tasks. Rather, project-based learning-incorporating situated practice and critical inquiry, and based on students' own cultural frameworks-will be required if students are to master the complex English literacy and communications skills required by the emerging informational economy and society.

The emergence of big data in educational contexts has led to new data-driven approaches to support informed decision making and efforts to improve educational effectiveness. Digital traces of student behavior promise more scalable and finer-grained understanding and support of learning processes, which were previously too costly to obtain with traditional data sources and methodologies. This synthetic review describes the affordances and applications of microlevel (e.g., clickstream data), mesolevel (e.g., text data), and macrolevel (e.g., institutional data) big data. For instance, clickstream data are often used to operationalize and understand knowledge, cognitive strategies, and behavioral processes in order to personalize and enhance instruction and learning. Corpora of student writing are often analyzed with natural language processing techniques to relate linguistic features to cognitive, social, behavioral, and affective processes. Institutional data are often used to improve student and administrational decision making through course guidance systems and early-warning systems. Furthermore, this chapter outlines current challenges of accessing, analyzing, and using big data. Such challenges include balancing data privacy and protection with data sharing and research, training researchers in educational data science methodologies, and navigating the tensions between explanation and prediction. We argue that addressing these challenges is worthwhile given the potential benefits of mining big data in education.