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August 2022 - Year 24 - Issue 4

ISSN 1755-9715

Investing in Technology in Language Education and Beyond

Mukhammadkhon Soliev is an international ELT teacher, teacher trainer and speaking examiner based in Samarkand, Uzbekistan. Also, he is a founder and director of Innovative Centre, authorized Cambridge English Exam Centre. E-mail: mukhammadkhon.soliev@innovativecentre.org

Parviz Subkhankulov is a Computer Science researcher at Duke University. He is a published author with the usage and role of technology in education and learning. He is currently working with industry professionals on Machine Learning and AI as a summer research scholar. E-mail: ps310@duke.edu

 

Abstract

We cannot conceive of international education without language instruction and evaluation. While the teaching and learning environment has evolved throughout time, neither the techniques nor the tools have responded. Due to the fact that Uzbekistan has become a hub for investment possibilities, this study explores the investment prospects and classroom applications of new technologies such as virtual reality (VR) conferences, simulations, and quizzes for language instruction. It also recommends using AI-powered technologies such as Automated Speech Recognition (ASR), Text Recognition, and Eye-Tracking to improve language evaluation.

 

Introduction

Outside of the classroom, technology has played and continues to play a crucial role in providing children with education, particularly language instruction. Using a mix of TV, radio, online, and mobile platforms, all nations could implement remote learning technology. The epidemic has also resulted in considerable learning losses. The crisis has exacerbated digital access disparities, proving that "business as usual" is insufficient to guarantee that all children have internet access. Although many low-income countries have been struggling to implement new technologies in education, investors are the ones who can be seen as a solution to this. Adapting educational systems is necessary. These concerns hint to the need to reimagine education in order to provide all students with an equitable, engaging, and joyful learning experience via the use of contemporary technologies in three unique and interdependent parts of education: teaching, learning, and assessment.

 

Technology in teaching

IT (Information Technology) has facilitated and enhanced the teaching process significantly. Since its implementation in classrooms and not only, the teaching procedure has become more convenient for teachers and instructors. Owing to such gadgets as interactive whiteboards and projectors, teachers can present information to students without printing out handouts to every student in a classroom. Other cases of IT contributing to teaching are distance learning and video conferencing technologies. Learning institutions have employed various technologies in education to adapt to a changing population and the outbreak of the pandemic of COVID-19 with unique demands. Online courses have allowed the majority of working and young adults to return to school and get additional degrees or certifications. It is feasible to attend an international college without ever leaving one's native country or room. Moreover, these technologies will allow professors to conduct virtual classrooms effectively and provide students with high-quality learning experiences wherever and at any time.

Numerous resources and legislative changes have been implemented to bring technology to K-12 schools, enabling all students to achieve success (Ritzhaupt et al., 2012). Students gain from easy access to information, fast learning, and many opportunities to apply their knowledge. It helps students to study new topics and deepen their understanding of complex concepts, particularly in STEM areas. However, attitudes and beliefs were described by broad phrases such as "the use of technology makes classes more student-centered." On the other hand, there are studies in which the relationship between the researched variables and technology usage has been conclusively proven (Karaca et al., 2013). Still, many instructors feel uneasy employing technology in the classroom. Some research imply that despite deploying technologies in different forms (instructional and application software), it is important to remember that instructors' use of subject- and context-dependent software is influenced more by confidence and comfort than by the matching utility impact. Utilization of instructional and application software improves as instructors become more at ease utilizing technology in the classroom. An impediment to technology integration, instructors' perceptions of how technology may be utilized are severely impacted by technological stress and anxiety (Shu et al., 2011; Tu et al., 2005). The overall impact of support from technology experts on teachers' usage of technology was statistically insignificant. The ability of teachers to incorporate technology into the classroom may be modeled along two paths: instructional and application software use (Dogan et al., 2021). Therefore, it is more important for school IT professionals to assist instructors in incorporating technology into their courses than for teachers to accept whatever software or hardware they can find (Dogan et al., 2021). Creating an atmosphere in which instructors feel comfortable utilizing technology in the classroom may increase student engagement. Consequently, the use of basic technology might make a substantial impact in enhancing students' capacity to absorb the content and material.

 

Technology in learning

Utilization of technology in education has played a major part in the academic careers of many pupils. The development and availability of new technology such as tablets, computers, interactive whiteboards, and the internet have increased interest in acquiring information via diverse means (Ataran et al., 2002). The adaptability and unlimited potential of technology attract students of both older and younger generations, resulting in increased learner engagement. In addition, one of the greatest comparative advantages of technology is its potential to evaluate students' initial learning levels and assign them to the most appropriate training and activities. This kind of technology may aid students in mastering essential skills and gaining more from their education by concentrating on their weak areas. In recent years, various software solutions have been categorized as CAL (Computer-Assisted Learning), yet many rely on a rather narrow distinction at an early stage (e.g., a diagnostic test) without further differentiation. These efforts are addressed in further detail below under "Expanding Practice Opportunities." CAL initiatives combine an initial diagnostic with dynamic adaptation (i.e., modifying the initial level of difficulty and the rate at which it increases or decreases based on whether learners' answers are correct or incorrect) to modify the initial level of difficulty and the rate at which it increases or decreases.

In recent years, Information and Communication Technology (aka ICT) has had a significant influence on many parts of society, and its potential to improve education has been highly lauded. As a result, educational institutions have been using technology to better the teaching and learning process for decades. There have been revolutionary changes to the education system with the broad adoption and implementation of digital technologies with curriculum changes benefiting education. The effort to incorporate technology into education in the early 1980s was tied to the introduction of computers to teach computer literacy to students (Moersch, 1995). In recent decades, however, ICT has been increasingly integrated into a larger educational reform framework. It attempts to improve students' self-learning, problem-solving, information searching and analysis, critical thinking, and communication, collaboration, and learning skills. Today's pupils are fundamentally different from prior generations since they grew up surrounded by digital technology, hence they are given names such as digital natives and net generations. These variations have prompted proposals for modifications to the educational system to meet the requirements of this new batch of students (Helsper & Eynon, 2010; Prensky, 2001; Selwyn, 2009; Tapscott, 1999). According to Tapscott, "the traditional technique [of didactic education] is inappropriate for meeting the intellectual, social, motivational, and emotional demands of the current generation" (Tapscott, 1998, p.131).

Adoption of ICT has the potential to expand access to and improve the quality of education in the setting of education. According to Tinio (2002), ICT has a substantial effect on education in terms of instructors' and students' information acquisition and absorption by encouraging active, creative, integrative, and evaluative learning (Tinio, 2002). In addition, the use of technology to manage learning material seems to have become normal among students. Students employ computer-mediated communication medium for file management, storage, and database repository, for example. Visual explanations of things that must be comprehended make learning enjoyable and interesting for children. They may participate more actively in class, and instructors can provide more dynamic and interesting sessions.E-readers are one of the most frequent and commonly used instances of IT in education. It is an electronic device that can hold hundreds of books digitally and allow students to read e-books anytime and anywhere. E-readers for individual reading have received favourable feedback from students, both expert and hesitant readers. The mobility and extended battery life of e-readers and the capacity to react to a text and clarify new terms may all contribute to favourable usage.

 

Technology in assessment

Core assessment technologies include natural language processing (NLP), automated voice recognition (ASR), text recognition, and eye tracking. Such processing technologies provide a plethora of new options and potential for language assessment. Primarily, the use of technology in language assessment has been motivated by a desire to enhance the efficiency of present testing procedures. Consequently, most of the ongoing effort has centered on this purpose. Computer-adaptive testing is an example of an efficiency-oriented method. Despite their potential use in several kinds of language tests, very little research has been undertaken in this sector. Therefore, test creators, researchers, users, and educators do not comprehend language evaluation well. Some English as a second language examinations provide as samples of the present assessment and evaluation capabilities for languages. All such systems employ statistical and linguistic approaches to achieve scoring by monitoring and locating significant language information in the examinees' responses, analyzing and combining that data, and optimising the prediction of scores acquired from human examiners.

One concern remains, however: how accurate is the scoring? In analyzing the automated scoring of essays on high-stakes ESL examinations, writing professionals often emphasize the necessity to show that the ratings assigned to examinees by the computer correspond to those a human rater would assign. Similarly, instructors who discuss software tools voice worries about the accuracy and relevance of the system's input to students. In both instances, the flaws may give a suitable beginning point for evaluating the assessment's validity. Nonetheless, both situations highlight the necessity for a broader perspective on assessment use. As several researchers have emphasized, the case for the legitimacy of scores generated by computer systems must go much beyond just proving a correlation between these scores and evaluations. A deeper examination of this kind of proof of validity suggests that it is not always essential and is often insufficient. In addition, different examiners may provide numerous responses and apply the criterion inconsistently.

Linguaskill is an example of an application of natural language processing (NLP) and automated voice recognition (ASR). Artificial intelligence-driven English as a second language examination. The method of scoring depends on a computer that identifies potentially significant characteristics from voice input in order to construct multiple regression scoring models. To make the regression model technically sound and to capture the concept of communicative, academic speaking ability as fully as feasible in terms of fluency, vocabulary, grammar, and pronunciation, the candidate's portions are cut. Examples of candidate features include, but are not limited to, the length of silences per word, the meaning of silence duration, speaking rate in terms per second, unique words divided by the duration of the entire transcribed segment, the average length of chunks in words, and the language model score.  

VR technologies have also become an integral element of education. Virtual platforms commonly imitate the classroom or laboratory environment for instructional reasons. Occasionally, though, they offer a safe setting for testing situations that would be too difficult or dangerous to execute in the actual world. Different forms of VR are used for different educational goals. The primary purpose of the first kind of VR platform is to illustrate the state of knowledge in a certain field of research, so supporting students in obtaining theoretical information, such as terminology, dates, facts, and scientific ideas. Consequently, it requires the least immersive setting, such as wall-based or monitor-based projection with special goggles or HMD with basic input devices such as a keyboard, mouse, touchscreen, or joystick. Typically, these scenarios include 3D visualization, training in dangerous circumstances, travel, and space exploration. A second sort of VR platform is used to teach practical skills based on prior knowledge. These situations are separated into theoretical knowledge presentations (in the form of a manual expression of requirements). The learner will next mimic or copy this portion as part of a practical assignment. This kind of application may demand a deeper level of immersion and control. This problem may need the use of external sensors such as Kinect or MYO Gesture Control Armband, sensor gloves, or specialized suits. The last kind of VR platform is intended to educate how to use learned information to solve difficulties. After gaining theoretical information, students are placed in a virtual environment to complete difficult tasks in such situations. Such a position may include establishing a problem, synthesizing a new phenomena, devising an action plan, and evaluating the situation based on certain criteria. This situation is used largely in medical sciences and engineering, and it often necessitates more advanced and precise teaching methods backed by haptic technologies.

The bulk of research has focused on the creation of automated scoring of essay replies and speech; nonetheless, it is clear that these technologies have the potential to improve language evaluation for a number of applications. Given the methods to language analysis for language assessments and the necessity for adequate validity studies to support varied assessment purposes, the variety of challenges should be clear.

 

Conclusion

It is not only about having the most up-to-date technology for digital transformation. Changing higher education's learning and commercial models in this period of technological advancement is a question of survival for some and a competitive requirement for everyone. Due to the pandemic's haste to remote learning, digital investment has risen to the top of strategic priorities, but too many schools are still moving too slowly, at their risk. Now is the moment for those in charge of their institution's digital transformation to take risks or risk being disrupted.

 

References

Ataran, M., globalisation information technology and training Institute for Cultural Research, aftabe Mehr, Tehran, p.23, 2002.

Dogan, S., Dogan, N.A. & Celik, I. Teachers’ skills to integrate technology in education: Two path models explaining instructional and application software use. Educ Inf Technol 26, 1311–1332 (2021). https://doi.org/10.1007/s10639-020-10310-4

Helsper, E.J. and Eynon, R. (2010), Digital natives: Where is the evidence?. British Educational Research Journal, 36: 503-520. https://doi.org/10.1080/01411920902989227

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Shu, Lisa & Gino, Francesca & Bazerman, Max. (2011). Dishonest Deed, Clear Conscience: When Cheating Leads to Moral Disengagement and Motivated Forgetting. Personality & social psychology bulletin. 37. 330-49. 10.1177/0146167211398138.

Selwyn, Neil. (2009). Faceworking: Exploring Students' Education-Related Use of Facebook. Learning. Media and Technology. 157-174. 10.1080/17439880902923622.

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Tapscott, D. (1999), New authorities of the digital age. Leader to Leader, 1999: 6-9. https://doi.org/10.1002/ltl.40619991302

 

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