QUALITY ASSURANCE FRAMEWORK: THE QUEST FOR QUALITY EDUCATION IN KAZAKHSTAN AND THE IMPORTANCE OF STUDENT VOICES

In the past decade, educational reforms have displayed an upsurge of interest in higher education. Promoting quality education has become a high priority issue in academia, as well as in policy-making units. There are many underlying reasons and precedents as to why quality education is of utmost importance in the Kazakhstani context. One of these reasons is the goal related to increasing prestige to become both competitive and attractive within the global network of higher education. Globally, by 2025, there will be an increase in the number of students who enroll in tertiary educational institutions. The expected figure is 263 million students, up from 100 million students in 2000 (Karaim, 2011). If we consider the dynamic nature of today's world, internationalization in edu cation (Ferreira, Vidal, & Vieira, 2014) has given rise to the inbound and outbound mobility of students, which poses multi-dimensional challenges for higher education. Thus, higher education institutions (HEIs) urgently need to meet the expectations of students to obtain quality education and recognize their academic documents within and beyond their geographical boundaries..

THE EFFECTS OF THE COVID-19 PANDEMIC ON THE WELL-BEING OF CHILDREN WITH AUTISM SPECTRUM DISORDER: PARENTS’ PERSPECTIVES

The COVID-19-related lockdown interrupted children’s learning progress and discontinued social learning and regular activities that children with autism spectrum disorder (ASD) rely on socially and physically. Negative consequences for children with ASD were reported far and wide. To investigate this problem in Kazakhstan, we conducted a mixed-methods study that drew on data from an online survey with 97 parents and semistructured interviews with 14 parents. While parent-report quantitative results suggest that children were likely to experience negative impacts of the pandemic due to disrupted educational and therapeutic services, qualitative findings confirm that they have experienced an elevated mental health and behavioral challenges during the lockdown. Remote educational and therapeutic services were not helpful as families coped with pandemic-caused problems on their own. We highlight that continued support and care during and after a crisis is vital not only for children with ASD but also for the families under-resourced mentally and socially

THE QUANTITATIVE CASE-BY-CASE ANALYSES OF THE SOCIO-EMOTIONAL OUTCOMES OF CHILDREN WITH ASD IN ROBOT-ASSISTED AUTISM THERAPY

With its focus on robot-assisted autism therapy, this paper presents case-by-case analyses of socio-emotional outcomes of 34 children aged 3–12 years old, with different cases of Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD).We grouped children by the following characteristics: ASD alone (n = 22), ASD+ADHD (n = 12), verbal (n = 11), non-verbal (n = 23), low-functioning autism (n = 24), and high-functioning autism (n = 10). This paper provides a series of separate quantitative analyses across the first and last sessions, adaptive and non-adaptive sessions, and parent and no-parent sessions, to present child experiences with the NAO robot, during play-based activities. The results suggest that robots are able to interact with children in social ways and influence their social behaviors over time. Each child with ASD is a unique case and needs an individualized approach to practice and learn social skills with the robot. We, finally, present specific child–robot intricacies that affect how children engage and learn over time as well as across different sessions

COGNITIVE LEARNING AND ROBOTICS: INNOVATIVE TEACHING FOR INCLUSIVITY

We present the interdisciplinary CoWriting Kazakh project in which a social robot acts as a peer in learning the new Kazakh Latin alphabet, to which Kazakhstan is going to shift from the current Kazakh Cyrillic by 2030. We discuss the past literature on cognitive learning and script acquisition in-depth and present a theoretical framing for this study. The results of word and letter analyses from two user studies conducted between 2019 and 2020 are presented. Learning the new alphabet through Kazakh words with two or more syllables and special native letters resulted in significant learning gains. These results suggest that reciprocal Cyrillic-to-Latin script learning results in considerable cognitive benefits due to mental conversion, word choice, and handwriting practices. Overall, this system enables school-age children to practice the new Kazakh Latin script in an engaging learning scenario. The proposed theoretical framework illuminates the understanding of teaching and learning within the multimodal robot-assisted script learning scenario and beyond its scope

A free/open-source hybrid morphological disambiguation tool for Kazakh

This paper presents the results of developing a morphological disambiguation tool for Kazakh. Starting with a previously developed rule-based approach, we tried to cope with the complex morphology of Kazakh by breaking up lexical forms across their derivational boundaries into inflectional groups and modeling their behavior with statistical methods. A hybrid rule-based/statistical approach appears to benefit morphological disambiguation demonstrating a per-token accuracy of 91% in running text

A free/open-source hybrid morphological disambiguation tool for Kazakh

This paper presents the results of developing a morphological disambiguation tool for Kazakh. Starting with a previously developed rule-based approach, we tried to cope with the complex morphology of Kazakh by breaking up lexical forms across their derivational boundaries into inflectional groups and modeling their behavior with statistical methods. A hybrid rule-based/statistical approach appears to benefit morphological disambiguation demonstrating a per-token accuracy of 91% in running text

Lessons Learned About Designing and Conducting Studies From HRI Experts

The field of human-robot interaction (HRI) research is multidisciplinary and requires researchers to understand diverse fields including computer science, engineering, informatics, philosophy, psychology, and more disciplines. However, it is hard to be an expert in everything. To help HRI researchers develop methodological skills, especially in areas that are relatively new to them, we conducted a virtual workshop, Workshop Your Study Design (WYSD), at the 2021 International Conference on HRI. In this workshop, we grouped participants with mentors, who are experts in areas like real-world studies, empirical lab studies, questionnaire design, interview, participatory design, and statistics. During and after the workshop, participants discussed their proposed study methods, obtained feedback, and improved their work accordingly. In this paper, we present 1) Workshop attendees’ feedback about the workshop and 2) Lessons that the participants learned during their discussions with mentors. Participants’ responses about the workshop were positive, and future scholars who wish to run such a workshop can consider implementing their suggestions. The main contribution of this paper is the lessons learned section, where the workshop participants contributed to forming this section based on what participants discovered during the workshop. We organize lessons learned into themes of 1) Improving study design for HRI, 2) How to work with participants - especially children -, 3) Making the most of the study and robot’s limitations, and 4) How to collaborate well across fields as they were the areas of the papers submitted to the workshop. These themes include practical tips and guidelines to assist researchers to learn about fields of HRI research with which they have limited experience. We include specific examples, and researchers can adapt the tips and guidelines to their own areas to avoid some common mistakes and pitfalls in their research

Lessons Learned About Designing and Conducting Studies From HRI Experts.

The field of human-robot interaction (HRI) research is multidisciplinary and requires researchers to understand diverse fields including computer science, engineering, informatics, philosophy, psychology, and more disciplines. However, it is hard to be an expert in everything. To help HRI researchers develop methodological skills, especially in areas that are relatively new to them, we conducted a virtual workshop, Workshop Your Study Design (WYSD), at the 2021 International Conference on HRI. In this workshop, we grouped participants with mentors, who are experts in areas like real-world studies, empirical lab studies, questionnaire design, interview, participatory design, and statistics. During and after the workshop, participants discussed their proposed study methods, obtained feedback, and improved their work accordingly. In this paper, we present 1) Workshop attendees' feedback about the workshop and 2) Lessons that the participants learned during their discussions with mentors. Participants' responses about the workshop were positive, and future scholars who wish to run such a workshop can consider implementing their suggestions. The main contribution of this paper is the lessons learned section, where the workshop participants contributed to forming this section based on what participants discovered during the workshop. We organize lessons learned into themes of 1) Improving study design for HRI, 2) How to work with participants - especially children -, 3) Making the most of the study and robot's limitations, and 4) How to collaborate well across fields as they were the areas of the papers submitted to the workshop. These themes include practical tips and guidelines to assist researchers to learn about fields of HRI research with which they have limited experience. We include specific examples, and researchers can adapt the tips and guidelines to their own areas to avoid some common mistakes and pitfalls in their research

Students` Perceptions and Experiences of Academic Kazakh in one Kazakhstani EMI University

Across many contexts, there has been an upsurge of interest in developing the requisite language skills to effectively communicate in academic discourse. This implies that language skills have specific features in academia that are inconsistent with everyday language (Christison & Krahnke, 1986; Cummins, 1999). Although academic language is commonly associated with English as the academic lingua franca, it is crucial to develop students’ academic skills in any language due to the emerging field of multilingual language education. In this sense, this study focuses on the use and development of Kazakh as an academic language which can be considered as an embodiment of the Kazakh language modernization. Thus, the current study explores students` perceptions and experiences of academic Kazakh in one Kazakhstani English-medium instruction (EMI) university. It also explores whether or not English for academic purposes (EAP) as a part of EMI influences students` Kazakh academic language development. This study used an interview-based qualitative research design in which eight students were interviewed after taking academic Kazakh language courses. The findings revealed that students perceive academic Kazakh as a scientific language aimed at developing the Kazakh-medium academic and research community in Kazakhstan. The majority of students believe that academic Kazakh courses are necessary for expanding the use of the Kazakh language in educational domains. It was also found that students` experiences are predominantly related to academic writing, which has developed under the influence of EAP, concerning writing style and organization. The significant challenge was to translate the English discipline-specific terminology due to the lack of equivalents in the Kazakh language, which might result in the limited use of discipline knowledge in the academic Kazakh communication. From a multilingual perspective, the study concludes that there are implications for academic biliteracy, whereby students can develop both Kazakh and English language skills for academic purposes

A LONG-TERM ENGAGEMENT WITH A SOCIAL ROBOT FOR AUTISM THERAPY

Social robots are increasingly being used as a mediator between a therapist and a child in autism therapy studies. In this context, most behavioural interventions are typically short term in nature. This paper describes a long-term study that was conducted with 11 children diagnosed with either Autism Spectrum Disorder (ASD) or ASD in co-occurrence with Attention Deficit Hyperactivity Disorder (ADHD). It uses a quantitative analysis based on behavioural measures, including engagement, valence, and eye gaze duration. Each child interacted with a robot on several occasions in which each therapy session was customized to a child’s reaction to robot behaviours. This paper presents a set of robot behaviours that were implemented with the goal to offer a variety of activities to be suitable for diverse forms of autism. Therefore, each child experienced an individualized robot assisted therapy that was tailored according to the therapist’s knowledge and judgement. The statistical analyses showed that the proposed therapy managed to sustain children’s engagement. In addition, sessions containing familiar activities kept children more engaged compared to those sessions containing unfamiliar activities. The results of the interviews with parents and therapists are discussed in terms of therapy recommendations. The paper concludes with some reflections on the current study as well as suggestions for future studies