Search results for: real-world learning experiences

Authors: Fakieh Alrabai

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This paper presents an experimental study designed to explore some of the learner’s individual and interpersonal factors (e.g. persistence, interest, regulation, satisfaction, appreciation, etc.) that Saudi learners experience when learning English as a Foreign Language and how learners’ perceptions of these factors influence various aspects of their motivation to learn English language. As part of the study, a 27-item structured survey was administered to a randomly selected sample of 105 Saudi learners from public schools and universities. Data collected through the survey were subjected to some basic statistical analyses, such as "mean" and "standard deviation". Based on the results from the analysis, a number of generalizations and conclusions are made in relation to how these inherent factors affect Saudi learners’ motivation to learn English as a foreign language. In addition, some recommendations are offered to Saudi academics on how to effectively make use of such factors, which may enable Saudi teachers and learners of English as a foreign language to achieve better learning outcomes in an area widely associated by Saudis with lack of success.

Keywords: persistence, interest, appreciation, satisfaction, SL/FL motivation

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Authors: E. Didaskalou, C. Roussi-Vergou, E. Andreou, G. Skrzypiec, P. Slee

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There has been growing interest lately, in the study of victimization among adolescent students in Greece and elsewhere with a view to improve school policies concerning anti-bullying practices. Researchers have recently focused on investigating the relationships between the extent of students’ victimization and the distinct mechanisms that they employ for coping with this particular problem. In particular, the emphasis has been placed on exploring the relationship between the coping strategies students use to counteract bullying, their sense of belonging at school, and extent of their victimization. Methods: Within the research framework outlined above, we set out to: a) examine the frequency of self-reported victimization among secondary school students, b) investigate the coping strategies employed by students when confronted with school bullying and c) explore any differences between bullied and non-bullied students with regard to coping strategies and school belongingness. The sample consisted of 860 from fifteen secondary public schools in central Greece. The schools were typical Greek secondary schools and the principals volunteered to participate in this study. Participants’ age ranged from 12 to 16 years. Measures: a) Exposure to Victimization: The frequency of victimization was directly located by asking students the question: ‘Over the last term, how often have you been bullied or harassed by a student or students at this high school?’ b) Coping Strategies: The ‘Living and Learning at School: Bullying at School’ was administered to students, c) School belongingness was assessed by the Psychological Sense of School Membership Scale, that students completed. Results: Regarding the frequency of self-reported victimization, 1.5% of the students reported being victimized every day, 2.8% most days of the week, 2.1% one or more days a week, 2.9% about once a week, 22.6% less than once a week and 68.1% never. The coping strategies that the participants employed for terminating their victimization included: a) adult support seeking, b) emotional coping/keep away from school, c) keeping healthy and fit, d) demonstrating a positive attitude towards the bully, d) peer support seeking, e) emotional out bursting, f) wishful thinking and self-blaming, g) pretending as if it is not happening, h) displaying assertive behaviors and i) getting away from the bullies. Bullied from non-bullied children did not differ as much in coping, as in feelings of being rejected in school. Discussion: The findings are in accordance with accumulated research evidence which points to a strong relationship between student perceptions of school belongingness and their involvement in bullying behaviors. We agree with the view that a positive school climate is likely to serve as a buffer that mitigates wider adverse societal influences and institutional attitudes which favor violence and harassment among peers.

Keywords: school bullying, school belonging, student coping strategies, victimization

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Authors: Marlon B. Espedillon

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This qualitative study examines practice teaching as an important component of teacher education and its entanglement with the teacher quality discourse. How the key actors -student teachers, supervising instructors, cooperating teachers, and school principals- construe teacher quality is essential in understanding how the student teachers articulate their voices and challenge the cultural myths in teacher education. The ethnographic method of research was used to provide an ecological picture of field experiences. Three cultural myths were uncovered based on the thematic analysis of the interview transcripts, observations, and documents.

Keywords: teacher quality, practice teaching, student teacher agency, cultural myths

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Authors: Ayse Ozturk Samur, Gozde Inal Kiziltepe

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No matter what level of education it is, starting a school is an exciting process as it includes new experiences. In this process, child steps into a different environment and institution except from the family institution which he was born into and feels secure. That new environment is different from home; it is a social environment which has its own rules, and involves duties and responsibilities that should be fulfilled and new vital experiences. The children who have a positive attitude towards school and like school are more enthusiastic and eager to participate in classroom activities. Moreover, a close relationship with the teacher enables the child to have positive emotions and ideas about the teacher and school and helps children adapt to school easily. In this study, it is aimed to identify children’s perceptions of academic competence, attitudes towards school and ideas about their teachers. In accordance with the aim a mixed method that includes both qualitative and quantitative data collection methods are used. The study is supported with qualitative data after collecting quantitative data. The study group of the research consists of randomly chosen 250 children who are 60-72 month old and attending a preschool institution in a city center located West Anatolian region of Turkey. Quantitative data was collected using Feelings about School scale. The scale consists of 12 items and 4 dimensions; school, teacher, mathematic, and literacy. Reliability and validity study for the scale used in the study was conducted by the researchers with 318 children who were 60-72 months old. For content validity experts’ ideas were asked, for construct validity confirmatory factor analysis was utilized. Reliability of the scale was examined by calculating internal consistency coefficient (Cronbach alpha). At the end of the analyses it was found that FAS is a valid and reliable instrument to identify 60-72 month old children’ perception of their academic competency, attitude toward school and ideas about their teachers. For the qualitative dimension of the study, semi-structured interviews were done with 30 children aged 60-72 month. At the end of the study, it was identified that children’s’ perceptions of their academic competencies and attitudes towards school was medium-level and their ideas about their teachers were high. Based on the semi structured interviews done with children, it is identified that they have a positive perception of school and teacher. That means quantitatively gathered data is supported by qualitatively collected data.

Keywords: feelings, preschool education, school, teacher, thoughts

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Authors: Pantaleon Lutta, Mohamed Sedky, Mohamed Hassan

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The inability of organizations to put in place management control measures for Internet of Things (IoT) complexities persists to be a risk concern. Policy makers have been left to scamper in finding measures to combat these security and privacy concerns. IoT forensics is a cumbersome process as there is no standardization of the IoT products, no or limited historical data are stored on the devices. This paper highlights why IoT forensics is a unique adventure and brought out the legal challenges encountered in the investigation process. A quadrant model is presented to study the conflicting aspects in IoT forensics. The model analyses the effectiveness of forensic investigation process versus the admissibility of the evidence integrity; taking into account the user privacy and the providers’ compliance with the laws and regulations. Our analysis concludes that a semi-automated forensic process using machine learning, could eliminate the human factor from the profiling and surveillance processes, and hence resolves the issues of data protection (privacy and confidentiality).

Keywords: cloud forensics, data protection Laws, GDPR, IoT forensics, machine Learning

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Authors: Jingwen Ou

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Writing for academic purposes in a second or foreign language is one of the most important and the most demanding skills to be mastered by non-native speakers. Traditionally, the EAP writing instruction at the tertiary level encompasses the teaching of academic genre knowledge, more specifically, the disciplinary writing conventions, the rhetorical functions, and specific linguistic features. However, one of the main sources of challenges in English academic writing for L2 students at the tertiary level can still be found in proficiency in academic discourse, especially vocabulary, academic register, and organization. Data-Driven Learning (DDL) is defined as “a pedagogical approach featuring direct learner engagement with corpus data”. In the past two decades, the rising popularity of the application of the data-driven learning (DDL) approach in the field of EAP writing teaching has been noticed. Such a combination has not only transformed traditional pedagogy aided by published DDL guidebooks in classroom use but also triggered global research on corpus use in EAP classrooms. This study endeavors to delineate a systematic review of research in the intersection of DDL and EAP writing instruction by conducting a systematic literature review on both indirect and direct DDL practice in EAP writing instructional settings in China. Furthermore, the review provides a synthesis of significant discoveries emanating from prior research investigations concerning Chinese university students’ perception of Data-Driven Learning (DDL) and the subsequent impact on their academic writing performance following corpus-based training. Research papers were selected from Scopus-indexed journals and core journals from two main Chinese academic databases (CNKI and Wanfang) published in both English and Chinese over the last ten years based on keyword searches. Results indicated an insufficiency of empirical DDL research despite a noticeable upward trend in corpus research on discourse analysis and indirect corpus applications for material design by language teachers. Research on the direct use of corpora and corpus tools in DDL, particularly in combination with genre-based EAP teaching, remains a relatively small fraction of the whole body of research in Chinese higher education settings. Such scarcity is highly related to the prevailing absence of systematic training in English academic writing registers within most Chinese universities' EAP syllabi due to the Chinese English Medium Instruction policy, where only English major students are mandated to submit English dissertations. Findings also revealed that Chinese learners still held mixed attitudes towards corpus tools influenced by learner differences, limited access to language corpora, and insufficient pre-training on corpus theoretical concepts, despite their improvements in final academic writing performance.

Keywords: corpus linguistics, data-driven learning, EAP, tertiary education in China

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Authors: Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu

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Causal inference from observational data is receiving wide applications in many fields. However, unidentifiable situations, where causal effects cannot be uniquely computed from observational data, pose critical barriers to applying causal inference to complicated real applications. In this paper, we develop a bounding method for estimating the average causal effect (ACE) under unidentifiable situations due to hidden confounders. We propose to parameterize the unknown exogenous random variables and structural equations of a causal model using neural networks and implicit generative models. Then, with an adversarial learning framework, we search the parameter space to explicitly traverse causal models that agree with the given observational distribution and find those that minimize or maximize the ACE to obtain its lower and upper bounds. The proposed method does not make any assumption about the data generating process and the type of the variables. Experiments using both synthetic and real-world datasets show the effectiveness of the method.

Keywords: average causal effect, hidden confounding, bound estimation, generative adversarial learning

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Authors: Sina Saadati

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Multiprocessors Systems-On-Chips (MPSOCs) are used widely on modern computers to execute sophisticated software and applications. These systems include different processors for distinct aims. Most of the proposed task schedulers attempt to improve energy consumption. In some schedulers, the processor's temperature is considered to increase the system's reliability and performance. In this research, we have proposed a new method for thermal-aware task scheduling which is based on an artificial neural network (ANN). This method enables us to consider a variety of factors in the scheduling process. Some factors like ambient temperature, season (which is important for some embedded systems), speed of the processor, computing type of tasks and have a complex relationship with the final temperature of the system. This Issue can be solved using a machine learning algorithm. Another point is that our solution makes the system intelligent So that It can be adaptive. We have also shown that the computational complexity of the proposed method is cheap. As a consequence, It is also suitable for battery-powered systems.

Keywords: task scheduling, MOSOC, artificial neural network, machine learning, architecture of computers, artificial intelligence

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Authors: Kingsley Agyapong

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Research conducted in recent years has delved into the concept of patient-perceived value within the context of co-creation, particularly in the realm of doctor-patient interactions within healthcare settings. However, existing scholarly discourse lacks exploration regarding the emergence of patient-derived value in the co-creation process, specifically within encounters involving patients and stakeholders such as doctors, nurses, pharmacists, and other healthcare professionals. This study aims to fill this gap by elucidating the perspectives of patients regarding the value they derive from their interactions with multiple stakeholders in the delivery of healthcare services. The fieldwork was conducted at a university clinic located in Ghana. Data collection procedures involved conducting 20 individual interviews with key informants on distinct value accrued from co-creation practices and interactions with stakeholders. The key informants consisted of patients receiving care at the university clinic during the Malaria Treatment Process. Three themes emerged from both the existing literature and the empirical data collected. The first theme, labeled as "patient value needs in co-creation," encapsulates elements such as communication effectiveness, interpersonal interaction quality, treatment efficacy, and enhancements to the overall quality of life experienced by patients during their interactions with healthcare professionals. The second theme, designated as "services that enhance patients' experience in value co-creation," pertains to patients' perceptions of services that contribute favourably to co-creation experiences, including initiatives related to health promotion and the provision of various in-house services that patients deem pertinent for augmenting their overall experiences. The third theme, titled "Challenges in the co-creation of patients' value," delineates obstacles encountered within the co-creation process, including health professionals' challenges in effectively following up with patients scheduled for review and prolonged waiting times for healthcare delivery. This study contributes to the patients' perceptions of value within the co-creation process during their interactions with service providers, particularly healthcare professionals. By gaining a deeper insight into this process, healthcare providers can enhance the delivery of patient-centered care, thereby leading to improved healthcare outcomes. The study further offers managerial implications derived from its findings, providing actionable insights for healthcare managers and policymakers aiming to optimize patient value creation in healthcare services. Furthermore, it suggests avenues for future research endeavors within healthcare settings.

Keywords: patient, healthcare, co-creation, malaria

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Authors: Maimuna Akram, Khadija Zia, Sohaib Naseer

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Pedagogical objectives and the nature of the course content may lead instructors to take varied approaches to selecting a student for the cold call, specifically in a studio setup where students work on different projects independently and show progress work time to time at scheduled critiques. Cold-calling often proves to be an effective tool in eliciting a response without enforcing judgment onto the recipients. While there is a mixed range of behavior exhibited by students who are cold-called, a classification of responses from anxiety-provoking to inspiring may be elicited; there is a need for a greater understanding of utilizing the exchanges in bringing about fruitful and engaging outcomes of studio discussions. This study aims to unravel the dimensions of utilizing the cold-call approach in a didactic exchange within studio pedagogy. A questionnaire survey was conducted in an undergraduate class at Arts and Design School. The impact of cold calling on students’ participation was determined through various parameters, including course choice, participation frequency, students’ comfortability, and teaching methodology. After analyzing the surveys, specific classroom teachers were interviewed to provide a qualitative perspective of the faculty. It was concluded that cold-calling increases students’ participation frequency and also increases preparation for class. Around 67% of students responded that teaching methods play an important role in learning activities and students’ participation during class discussions. 84% of participants agreed that cold calling is an effective way of learning. According to research, cold-calling can be done in large numbers without making students uncomfortable. As a result, the findings of this study support the use of this instructional method to encourage more students to participate in class discussions.

Keywords: active learning, class discussion, class participation, cold calling, pedagogical methods, student engagement

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Authors: Piumi L. Denagamage, Vibusha Madanayake

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At the end of a 30-year civil war in Sri Lanka in 2009, Non-Governmental Organizations (NGOs) played a prominent role in post-war development and peacebuilding. Women were a major “beneficiary” of NGO activities on socio-economic empowerment, capacity building for advocacy, and grassroots participation in activism. Undoubtedly, their contribution to Sri Lanka’s post-war transition is tremendous. As development practitioners and researchers who have worked closely with several international and national NGOs in Sri Lanka’s post-war setting, the authors, while practicing self-reflexivity, intend to theorize the grey literature prepared by NGOs against the theoretical frameworks of Transnational and Third World feminisms. Using examples of the grassroots activities conducted by the NGOs with war-affected women, the paper questions whether Colombo-based feminism represents the lived realities of grassroots women at the transnational level. It argues that Colombo-based feminists use their power and exposure to Western feminist approaches to portray diverse forms of oppression women face at grassroots levels, their needs for advocacy, and different modes of resistance on the ground. Many NGOs depend on international donor funding for their grassroots work, which also contributes to their utilization of Western-led knowledge. Despite their efforts to “save marginalized women from oppression,” these modes of intervention are often rejected by the public, including women at local levels. This has also resulted in the rejection of feminism entirely as a culturally root-less alien Western ideology. The analysis connects with the Transnational and Third World theoretical feminist perspectives to problematize the power relations between Western knowledge systems and the lived experiences of grassroots women in the peacebuilding process through NGO activism in Sri Lanka. It also emphasizes that the infiltration of Western knowledge through NGOs has led to the participation of grassroots women only through adjustments of their lived experiences to match the alien knowledge rather than theorizing based on their own lived realities. While sharing a concern that NGOs’ power to adopt Western knowledge systems is often unchecked and unmitigated, the paper signifies the importance of adopting the methods of alternative theorizing to ensure meaningful participation of Third World women in peacebuilding.

Keywords: alternative theorizing, colombo-based feminism, grassroots women in peacebuilding, NGO activism, transnational and third world feminisms

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Authors: Candela Contero Urgal

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Using realia to teach English for Specific Purposes (ESP) is a must, as it is thought to be designed to meet the students’ real needs in their professional life. Teachers are then expected to offer authentic materials and set students in authentic contexts where their learning outcomes can be highly meaningful. One way of engaging students is using social networks as a way to bridge the gap between their everyday life and their ESP learning outcomes. It is in ESP, particularly in Business English teaching, that our study focuses, as the ongoing process of digitalization is leading firms to use social media to communicate with potential clients. The present paper is aimed at carrying out a case study in which different digital tools are employed as a way to offer a collection of formats businesses are currently using so as to internationalize and advertise their products and services. A secondary objective of our study will then be to progress on the development of multidisciplinary competencies students are to acquire during their degree. A two-phased study will be presented. The first phase will cover the analysis of course tasks accomplished by undergraduate students at the University of Cadiz (Spain) in their third year of the Degree in Business Management and Administration by comparing the results obtained during the years 2019 to 2021. The second part of our study will present a survey conducted to these students in 2021 and 2022 so as to verify their interest in learning new ways to digitalize as well as internationalize their future businesses. Findings will confirm students’ interest in working with updated realia in their Business English lessons, as a consequence of their strong belief in the necessity to have authentic contexts and didactic resources. Despite the limitations social media can have as a means to teach business English, students will still find it highly beneficial since it will foster their familiarisation with the digital tools they will need to use when they get to the labour market.

Keywords: English for specific purposes, business English, internationalization of higher education, foreign language teaching

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Authors: Alex Elentukh

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The paper is based on data collected from final exams administered during five years of teaching the graduate course in software engineering. The visualization instrument with four distinct personas has been used to improve the effectiveness of each class. The study offers a plethora of clues toward students' behavioral preferences. Diversity among students (professional background, physical proximity) is too significant to assume a single face of a learner. This is particularly true for a body of online graduate students in computer science. Conclusions of the study (each learner is unique, and each class is unique) are extrapolated to demystify the notion of an 'average software engineer.' An immediate direction for an educator is to ensure a course applies to a wide audience of very different individuals. On the other hand, a student should be clear about his/her abilities and preferences - to follow the most effective learning path.

Keywords: K.3.2 computer and information science education, learner profiling, adaptive learning, software engineering

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Authors: Chris Procter

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There is a significant debate on the role of University education in developing or teaching employability skills. Should higher education attempt to do this? Is it the best place? Is it able to do so? Different views abound, but the question is wrongly posed – one of the reasons that previous employability initiatives foundered (e.g., in the UK). Our role is less to teach than to guide, less to develop and more to help articulate: “the mind is not a vessel to be filled, but a fire to be lit” (Plutarch). This paper then addresses how this can be achieved taking into account criticism of employability initiatives as well as relevant learning theory. It discusses the experience of a large module which involved students being assessed on all stages of application for a live job description together with reflection on their professional development. The assessment itself adopted a Patchwork Text approach as a vehicle for learning. Students were guided to evaluate their strengths and areas to be developed, articulate their competencies, and reflect upon their development, moving on to new Thresholds of Employability. The paper uses the student voices to express the progress they made. It concludes that employability can and should be an effective part of the higher education curriculum when designed to encourage students to confidently articulate their competencies and take charge of their own professional development.

Keywords: competencies, employability, patchwork assessment, threshold concepts

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Authors: Mohammad Haghighi, Amineh Akhondi, Leila Jahangard, Mohammad Ahmadpanah, Masoud Ansari

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Background: According to the recent estimation, approximately 4%-12% percent of Iranians have difficulty in learning to read and spell possibly as a result of developmental dyslexia. The study was planned to investigate spelling error patterns among Persian children with developmental dyslexia and compare that with the errors exhibited by control groups Participants: 90 students participated in this study. 30 students from Grade level five, diagnosed as dyslexics by professionals, 30 normal 5th Grade readers and 30 younger normal readers. There were 15 boys and 15 girls in each of the groups. Qualitative and quantitative methods for analysis of errors were used. Results and conclusion: results of this study indicate similar spelling error profiles among dyslexics and the reading level matched groups, and these profiles were different from age-matched group. However, performances of dyslexic group and reading level matched group were different and inconsistent in some cases.

Keywords: spelling, error types, developmental dyslexia, Persian, writing system, learning disabilities, processing

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Authors: Zarah M. Bello, Nathan Baddoo, Mariana Lilley, Paul Wernick

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In this paper, we present findings from a multi-part study to evaluate candidate elements reflecting the level of digital capability maturity (DCM) in higher education and the relationship between these elements. We will use these findings to propose a model of DCM for educational institutions. We suggest that the success of learning in higher education is dependent in part on the level of maturity of digital capabilities of institutions as well as the abilities of learners and those who support the learning process. It is therefore important to have a good understanding of the elements that underpin this maturity as well as their impact and interactions in order to better exploit the benefits that technology presents to the modern learning environment and support its continued improvement. Having identified ten candidate elements of digital capability that we believe support the level of a University’s maturity in this area as well as a number of relevant stakeholder roles, we conducted two studies utilizing both quantitative and qualitative research methods. In the first of these studies, 85 electronic questionnaires were completed by various stakeholders in a UK university, with a 100% response rate. We also undertook five in-depth interviews with management stakeholders in the same university. We then utilized statistical analysis to process the survey data and conducted a textual analysis of the interview transcripts. Our findings support our initial identification of candidate elements and support our contention that these elements interact in a multidimensional manner. This multidimensional dynamic suggests that any proposal for improvement in digital capability must reflect the interdependency and cross-sectional relationship of the elements that contribute to DCM. Our results also indicate that the notion of DCM is strongly data-centric and that any proposed maturity model must reflect the role of data in driving maturity and improvement. We present these findings as a key step towards the design of an operationalisable DCM maturity model for universities.

Keywords: digital capability, elements, maturity, maturity framework, university

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Authors: Francesca Perri

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This paper describes a proposal for a teachers’ training course, focused on the introduction of corpora in the EFL didactics (English as a foreign language) of some Italian secondary schools. The training course is conceived as a part of a TEDD participant’s five months internship. TEDD (Technologies for Education: diversity and devices) is an advanced course held by the Department of Engineering and Information Technology at the University of Trento, Italy. Its main aim is to train a selected, heterogeneous group of graduates to engage with the complex interdependence between education and technology in modern society. The educational approach draws on a plural coexistence of various theories as well as socio-constructivism, constructionism, project-based learning and connectivism. TEDD educational model stands as the main reference source to the design of a formative course for EFL teachers, drawing on the digitalization of didactics and creation of learning interactive materials for L2 intermediate students. The training course lasts ten hours, organized into five sessions. In the first part (first and second session) a series of guided and semi-guided activities drive participants to familiarize with corpora through the use of a digital tools kit. Then, during the second part, participants are specifically involved in the realization of a ML (Mistakes Laboratory) where they create, develop and share digital activities according to their teaching goals with the use of corpora, supported by the digital facilitator. The training course takes place into an ICT laboratory where the teachers work either individually or in pairs, with a computer connected to a wi-fi connection, while the digital facilitator shares inputs, materials and digital assistance simultaneously on a whiteboard and on a digital platform where participants interact and work together both synchronically and diachronically. The adoption of good ICT practices is a fundamental step to promote the introduction and use of Corpus Linguistics in EFL teaching and learning processes, in fact dealing with corpora not only promotes L2 learners’ critical thinking and orienteering versus wild browsing when they are looking for ready-made translations or language usage samples, but it also entails becoming confident with digital tools and activities. The paper will explain reasons, limits and resources of the pedagogical approach adopted to engage EFL teachers with the use of corpora in their didactics through the promotion of digital practices.

Keywords: digital didactics, education, language learning, teacher training

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Authors: Ka Lei Au

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The Dalcroze method has been emerging in music classrooms, and music teachers are encouraged to integrate music and movement in their teaching. Music programs in colleges in Hong Kong have been introducing method courses such as Orff and Dalcroze method in music teaching as teacher’s education program. Since the targeted students of the course are music teachers who are making the decision of what approach to use in their classroom, their perception is significantly valued to identify how this approach is applicable in their teaching in regards to the teaching and learning culture and environment. This qualitative study aims to explore how the Dalcroze method as a teacher’s education course is perceived by music teachers from three aspects: 1) application in music teaching, 2) self-enhancement, 3) expectation. Through the lens of music teachers, data were collected from 30 music teachers who are taking the Dalcroze method course in music teaching in Hong Kong by the survey. The findings reveal the value and their intention of the Dalcroze method in Hong Kong. It also provides a significant reference for better development of such courses in the future in adaption to the culture, teaching and learning environment and teacher’s, student’s and parent’s perception of this approach.

Keywords: Dalcroze method, music teaching, perception, self-enhancement, teacher’s education

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Authors: Leah Ning

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This paper discusses the development of a machine learning algorithm that accurately detects metastatic breast cancer (cancer has spread elsewhere from its origin part) in selected images that come from pathology scans of lymph node sections. Being able to develop an accurate artificial intelligence (AI) algorithm would help significantly in breast cancer diagnosis since manual examination of lymph node scans is both tedious and oftentimes highly subjective. The usage of AI in the diagnosis process provides a much more straightforward, reliable, and efficient method for medical professionals and would enable faster diagnosis and, therefore, more immediate treatment. The overall approach used was to train a convolution neural network (CNN) based on a set of pathology scan data and use the trained model to binarily classify if a new scan were benign or malignant, outputting a 0 or a 1, respectively. The final model’s prediction accuracy is very high, with 100% for the train set and over 70% for the test set. Being able to have such high accuracy using an AI model is monumental in regard to medical pathology and cancer detection. Having AI as a new tool capable of quick detection will significantly help medical professionals and patients suffering from cancer.

Keywords: breast cancer detection, AI, machine learning, algorithm

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Authors: Bryan Young, Andrew Wodehouse, Marion Sheridan

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The availability of working memory has long been identified as a critical aspect of an instructional design. Many conventional instructional procedures impose irrelevant or unrelated cognitive loads on the learner due to the fact that they were created without contemplation, or understanding, of cognitive work load. Learning to physically operate traditional products can be viewed as a learning process akin to any other. As such, many of today's products, such as cars, boats, and planes, which have traditional controls that predate modern user-centered design techniques may be imposing irrelevant or unrelated cognitive loads on their operators. The goal of the research was to investigate the fundamental relationships between physical inputs, resulting actions, and learnability. The results showed that individuals can quickly adapt to input/output reversals across dimensions, however, individuals struggle to cope with the input/output when the dimensions are rotated due to the resulting increase in cognitive load.

Keywords: cognitive load theory, instructional design, physical product interactions, usability design

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Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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Authors: Yun Chan Lee

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Background: End-of-life care is a large area of all nursing practice and student nurses are likely to meet dying patients in many placement areas. It is therefore important to understand the emotional responses and coping strategies of student nurses in order for nursing education systems to have some appreciation of how nursing students might be supported in the future. Methodology: This research used a qualitative phenomenological approach. Six student nurses understanding a degree-level adult nursing course were interviewed. Their responses to questions were analyzed using interpretative phenomenological analysis. Finding: The findings identified 3 main themes. First, the common experience of ‘unpreparedness’. A very small number of participants felt that this was unavoidable and that ‘no preparation is possible’, the majority felt that they were unprepared because of ‘insufficient input’ from the university and as a result of wider ‘social taboos’ around death and dying. The second theme showed that emotions were affected by ‘the personal connection to the patient’ and the important sub-themes of ‘the evoking of memories’, ‘involvement in care’ and ‘sense of responsibility’. The third theme, the coping strategies used by students, seemed to fall into two broad areas those ‘internal’ with the student and those ‘external’. In terms of the internal coping strategies, ‘detachment’, ‘faith’, ‘rationalization’ and ‘reflective skills’ are the important components of this part. Regarding the external coping strategies, ‘clinical staff’ and ‘the importance of family and friends’ are the importance of accessing external forms of support. Implication: It is clear that student nurses are affected emotionally by caring for dying patients and many of them have apprehension even before they begin on their placements but very often this is unspoken. Those anxieties before the placement become more pronounced during and continue after the placements. This has implications for when support is offered and possibly its duration. Another significant point of the study is that participants often highlighted their wish to speak to qualified nurses after their experiences of being involved in end-of-life care and especially when they had been present at the time of death. Many of the students spoke that qualified nurses were not available to them. This seemed to be due to a number of reasons. Because the qualified nurses were not available, students had to make use of family members and friends to talk to. Consequently, the implication of this study is not only to educate student nurses but also to educate the qualified mentors on the importance of providing emotional support to students.

Keywords: nursing students, coping strategies, end-of-life care, emotional responses

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Authors: Hoa Pham

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The literature on language teaching and second language acquisition has been largely driven by monolingual ideology with a common assumption that a second language (L2) is best taught and learned in the L2 only. The current study challenges this assumption by reporting learners' positive perceptions of tertiary level teachers' code switching practices in Vietnam. The findings of this study contribute to our understanding of code switching practices in language classrooms from a learners' perspective. Data were collected from student participants who were working towards a Bachelor degree in English within the English for Business Communication stream through the use of focus group interviews. The literature has documented that this method of interviewing has a number of distinct advantages over individual student interviews. For instance, group interactions generated by focus groups create a more natural environment than that of an individual interview because they include a range of communicative processes in which each individual may influence or be influenced by others - as they are in their real life. The process of interaction provides the opportunity to obtain the meanings and answers to a problem that are "socially constructed rather than individually created" leading to the capture of real-life data. The distinct feature of group interaction offered by this technique makes it a powerful means of obtaining deeper and richer data than those from individual interviews. The data generated through this study were analysed using a constant comparative approach. Overall, the students expressed positive views of this practice indicating that it is a useful teaching strategy. Teacher code switching was seen as a learning resource and a source supporting language output. This practice was perceived to promote student comprehension and to aid the learning of content and target language knowledge. This practice was also believed to scaffold the students' language production in different contexts. However, the students indicated their preference for teacher code switching to be constrained, as extensive use was believed to negatively impact on their L2 learning and trigger cognitive reliance on the L1 for L2 learning. The students also perceived that when the L1 was used to a great extent, their ability to develop as autonomous learners was negatively impacted. This study found that teacher code switching was supported in certain contexts by learners, thus suggesting that there is a need for the widespread assumption about the monolingual teaching approach to be re-considered.

Keywords: codeswitching, L1 use, L2 teaching, learners’ perception

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Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

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The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

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Authors: Tugba Altin

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In a time characterized by escalating climate change impacts, communities globally face extreme events with deep-reaching tangible and intangible consequences. At the intersection of these phenomena lies the profound impact on the cultural and emotional connections that individuals forge with their environments. This study casts a spotlight on the Lytton Creek Fire of 2021, showcasing it as an exemplar of both the visible destruction brought by such events and the more covert yet deeply impactful disturbances to place attachment (PA). Defined as the emotional and cognitive bond individuals form with their surroundings, PA is critical in comprehending how such catastrophic events reshape cultural identity and the bond with the land. Against the stark backdrop of the Lytton Creek Fire's devastation, the research seeks to unpack the multilayered dynamics of PA amidst the tangible wreckage and the intangible repercussions such as emotional distress and disrupted cultural landscapes. Delving deeper, it examines how affected populations renegotiate their affiliations with these drastically altered environments, grappling with both the tangible loss of their homes and the intangible challenges to solace, identity, and community cohesion. This exploration is instrumental in the broader climate change narrative, as it offers crucial insights into how these personal-place relationships can influence and shape climate adaptation and recovery strategies. Departing from traditional data collection methodologies, this study adopts an interpretive phenomenological approach enriched by hermeneutic insights and places the experiences of the Lytton community and its co-researchers at its core. Instead of conventional interviews, innovative methods like walking audio sessions and photo elicitation are employed. These techniques allow participants to immerse themselves back into the environment, reviving and voicing their memories and emotions in real-time. Walking audio captures reflections on spatial narratives after the trauma, whereas photo voices encapsulate the intangible emotions, presenting a visual representation of place-based experiences. Key findings emphasize the indispensability of addressing both the tangible and intangible traumas in community recovery efforts post-disaster. The profound changes to the cultural landscape and the subsequent shifts in PA underscore the need for holistic, culturally attuned, and emotionally insightful adaptation strategies. These strategies, rooted in the lived experiences and testimonies of the affected individuals, promise more resonant and effective recovery efforts. The research further contributes to climate change discourse, highlighting the intertwined pathways of tangible reconstruction and the essentiality of emotional and cultural rejuvenation. Furthermore, the use of participatory methodologies in this inquiry challenges traditional research paradigms, pointing to potential evolutionary shifts in qualitative research norms. Ultimately, this study underscores the need for a more integrative approach in addressing the aftermath of environmental disasters, ensuring that both physical and emotional rebuilding are given equal emphasis.

Keywords: place attachment, community recovery, disaster reponse, sensory responses, intangible traumas, visual methodologies

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Authors: Masoomeh Alsadat Mirshafaei

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The present study aims to explore the effect of an 8-week aerobic training regimen combined with cinnamon extract on serum irisin and leptin levels in insulin-resistant rats. Additionally, this research leverages various machine learning (ML) and deep learning (DL) algorithms to model the complex interdependencies between exercise, nutrition, and metabolic markers, offering a groundbreaking approach to obesity and diabetes research. Forty-eight Wistar rats were selected and randomly divided into four groups: control, training, cinnamon, and training cinnamon. The training protocol was conducted over 8 weeks, with sessions 5 days a week at 75-80% VO2 max. The cinnamon and training-cinnamon groups were injected with 200 ml/kg/day of cinnamon extract. Data analysis included serum data, dietary intake, exercise intensity, and metabolic response variables, with blood samples collected 72 hours after the final training session. The dataset was analyzed using one-way ANOVA (P<0.05) and fed into various ML and DL models, including Support Vector Machines (SVM), Random Forest (RF), and Convolutional Neural Networks (CNN). Traditional statistical methods indicated that aerobic training, with and without cinnamon extract, significantly increased serum irisin and decreased leptin levels. Among the algorithms, the CNN model provided superior performance in identifying specific interactions between cinnamon extract concentration and exercise intensity, optimizing the increase in irisin and the decrease in leptin. The CNN model achieved an accuracy of 92%, outperforming the SVM (85%) and RF (88%) models in predicting the optimal conditions for metabolic marker improvements. The study demonstrated that advanced ML and DL techniques could uncover nuanced relationships and potential cellular responses to exercise and dietary supplements, which is not evident through traditional methods. These findings advocate for the integration of advanced analytical techniques in nutritional science and exercise physiology, paving the way for personalized health interventions in managing obesity and diabetes.

Keywords: aerobic training, cinnamon extract, insulin resistance, irisin, leptin, convolutional neural networks, exercise physiology, support vector machines, random forest

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Authors: Robert Pocklington

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Most current language courses expect students to be ‘vocational’, sacrificing their free time in order to learn. However, pupils with a full-time job, or bringing up children, hardly have a spare moment. Others just need the language as a tool or a qualification, as if it were book-keeping or a driving license. Then there are children in unstructured families whose stressful life makes private study almost impossible. And the countless parents whose evenings and weekends have become a nightmare, trying to get the children to do their homework. There are many arguments against homework being a necessity (rather than an optional extra for more ambitious or dedicated students), making a clear case for teaching methods which facilitate full learning of the key content within the classroom. A methodology which could be described as Programmed Mastery Learning has been used at Fluency Language Academy (Spain) since 1992, to teach English to over 4000 pupils yearly, with a staff of around 100 teachers, barely requiring homework. The course is structured according to the tenets of Programmed Learning: small manageable teaching steps, immediate feedback, and constant successful activity. For the Mastery component (not stopping until everyone has learned), the memorisation and practice are entrusted to flashcard-based drilling in the classroom, leading all students to progress together and develop a permanently growing knowledge base. Vocabulary and expressions are memorised using flashcards as stimuli, obliging the brain to constantly recover words from the long-term memory and converting them into reflex knowledge, before they are deployed in sentence building. The use of grammar rules is practised with ‘cue’ flashcards: the brain refers consciously to the grammar rule each time it produces a phrase until it comes easily. This automation of lexicon and correct grammar use greatly facilitates all other language and conversational activities. The full B2 course consists of 48 units each of which takes a class an average of 17,5 hours to complete, allowing the vast majority of students to reach B2 level in 840 class hours, which is corroborated by an 85% pass-rate in the Cambridge University B2 exam (First Certificate). In the past, studying for qualifications was just one of many different options open to young people. Nowadays, youngsters need to stay at school and obtain qualifications in order to get any kind of job. There are many students in our classes who have little intrinsic interest in what they are studying; they just need the certificate. In these circumstances and with increasing government pressure to minimise failure, teachers can no longer think ‘If they don’t study, and fail, its their problem’. It is now becoming the teacher’s problem. Teachers are ever more in need of methods which make their pupils successful learners; this means assuring learning in the classroom. Furthermore, homework is arguably the main divider between successful middle-class schoolchildren and failing working-class children who drop out: if everything important is learned at school, the latter will have a much better chance, favouring inclusiveness in the language classroom.

Keywords: flashcard drilling, fluency method, mastery learning, programmed learning, teaching English as a foreign language

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Authors: Intan Azura Mokhtar, Yaacob Ibrahim

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In recent years, learning about sustainable development and sustainability has become an increasingly significant component in universities’ degree programmes and curricula. As the world comes together and races to fulfil the 17 United Nations’ sustainable development goals (SDGs) by the year 2030, our educational curricula and landscapes simultaneously evolve to integrate lessons and opportunities for sustainable development and sustainability to redefine our university education and set the trajectory for our young people to take the lead in co-creating solutions for a better world. In this paper, initiatives and projects that revolved around themes of sustainable development and sustainability in a young university in Singapore are discussed. These initiatives and projects were curated by a new centre in the university that focuses on community leadership, social innovation, and service learning and was led by the university’s academic staff. The university’s undergraduate students were also involved in these initiatives and projects and played an active role in reaching out to and engaging members of different segments of the community – to better understand their needs and concerns and to co-create with them relevant and sustainable solutions that generate positive social impact.

Keywords: singapore, sustainable development, sustainability, undergraduate education

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Authors: Dr. Luigi Iannacci

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This research critically explores the current educational landscape with respect to special education and dominant deficit/medical model discourses that continue to forward unresponsive problematic approaches to teaching students with disabilities. Asset-oriented perspectives and social/critical models of disability are defined and explicated in order to offer alternatives to these dominant discourses. To that end, a framework that draws on Brian Camborne’s conditions of learning and applications of his work in relation to instruction conceptualize learning conditions and their significance to students with special needs. Methodologically, the research is designed as Critical Narrative Inquiry (CNI). Critical incidents, interviews, documents, artefacts etc. are drawn on and narratively constructed to explore how disability is presently configured in language, discourses, pedagogies and interactions with students deemed disabled. This data was collected using ethnographic methods and as such, through participant-observer field work that occurred directly in classrooms. This narrative approach aims to make sense of complex classroom interactions and ways of reconceptualizing approaches to students with special needs. CNI is situated in the critical paradigm and primarily concerned with culture, language and participation as issues of power in need of critique with the intent of change in the direction of social justice. Research findings highlight the ways in which Cambourne’s learning conditions, such as demonstration, approximation, engagement, responsibility, immersion, expectation, employment (transfer, use), provide a clear understanding of what is central to and constitutes a responsive and inclusive this instructional frame. Examples of what each of these conditions look like in practice are therefore offered in order to concretely demonstrate the ways in which various pedagogical choices and questions can enable classroom spaces to be responsive to the assets and challenges students with special needs have and experience. These particular approaches are also illustrated through an exploration of multiliteracies theory and pedagogy and what this research and approach allows educators to draw on, facilitate and foster in terms of the ways in which students with special needs can make sense of and demonstrate their understanding of skills, content and knowledge. The contextual information, theory, research and instructional frame focused on throughout this inquiry ultimately demonstrate what inclusive classroom spaces and practice can look like. These perspectives and conceptualizations are in stark contrast to dominant deficit driven approaches that ensure current pedagogically impoverished teaching focused on narrow, limited and limiting understandings of special needs learners and their ways of knowing and acquiring/demonstrating knowledge.

Keywords: asset-oriented approach, social/critical model of disability, conditions for learning and teaching, students with special needs

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