Search results for: collaborative learning

Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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Authors: Malephole Philomena Sefotho

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Nowadays, it is a fact that the majority of people, worldwide, are bilingual rather than monolingual due to the surge of globalisation and mobility. Consequently, bilingual education is a topical issue of discussion among researchers. Several studies that have focussed on it have highlighted the importance and need for incorporating learners’ linguistic repertoires in multilingual classrooms and move away from the colonial approach which is a monolingual bias – one language at a time. Researchers pointed out that a systematic approach that involves the concurrent use of languages and not a separation of languages must be implemented in bilingual classroom settings. Translanguaging emerged as a systematic approach that assists learners to make meaning of their world and it involves allowing learners to utilize all their linguistic resources in their classrooms. The South African language policy also room for diverse languages use in bi/multilingual classrooms. This study, therefore, sought to explore how teachers apply translanguaging in bilingual classrooms in incorporating learners’ linguistic repertoires. It further establishes teachers’ perspectives in the use of more than one language in teaching and learning. The participants for this study were language teachers who teach at bilingual primary schools in Johannesburg in South Africa. Semi-structured interviews were conducted to establish their perceptions on the concurrent use of languages. Qualitative research design was followed in analysing data. The findings showed that teachers were reluctant to allow translanguaging to take place in their classrooms even though they realise the importance thereof. Not allowing bilingual learners to use their linguistic repertoires has resulted in learners’ negative attitude towards their languages and contributed in learners’ loss of their identity. This article, thus recommends a drastic change to decolonised approaches in teaching and learning in multilingual settings and translanguaging as a decolonial move where learners are allowed to translanguage freely in their classroom settings for better comprehension and making meaning of concepts and/or related ideas. It further proposes continuous conversations be encouraged to bring eminent cultural and linguistic genocide to a halt.

Keywords: bilingualism, decolonisation, linguistic repertoires, translanguaging

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Authors: Sahar Navabakhsh, Rokia Raslan, Yair Schwartz

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Decision-making on regeneration of housing estates, whether to refurbish or re-build, has been mostly triggered by economic factors. To enable sustainable growth, it is vital that environmental and social impacts of different scenarios are also taken into account. The methodology used to include all the three sustainable development pillars is called Life Cycle Sustainability Assessment (LCSA), which comprises of Life Cycle Assessment (LCA) for the assessment of environmental impacts of buildings. Current practice of LCA is regularly conducted post design stage and by sustainability experts. Not only is undertaking an LCA at this stage less effective, but issues such as the limited scope for the definition and assessment of environmental impacts, the implication of changes in the system boundary and the alteration of each of the variable metrics, employment of different Life Cycle Impact Assessment Methods and use of various inventory data for Life Cycle Inventory Analysis can result in considerably contrasting results. Given the niche nature and scarce specialist domain of LCA of buildings, the majority of the stakeholders do not contribute to the generation or interpretation of the impact assessment, and the results can be generated and interpreted subjectively due to the mentioned uncertainties. For an effective and democratic assessment of environmental impacts, different stakeholders, and in particular the community and design team should collaborate in the process of data collection, assessment and analysis. This paper examines and evaluates a participatory approach to LCSA through the analysis of a case study of a housing estate in South West London. The study has been conducted throughout tier-based collaborative methods to collect and share data through surveys and co-design workshops with the community members and the design team as the main stakeholders. The assessment of lifecycle impacts is conducted throughout the process and has influenced the decision-making on the design of the Community Plan. The evaluation concludes better assessment transparency and outcome, alongside other socio-economic benefits of identifying and engaging the most contributive stakeholders in the process of conducting LCSA.

Keywords: life cycle assessment, participatory LCA, life cycle sustainability assessment, participatory processes, decision-making, housing estate regeneration

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Authors: Mikael Soini, Kari Björn

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Metropolia University of Applied Sciences (MUAS) Information and Communication Technology (ICT) Degree Programme provides full-time Bachelor-level undergraduate studies. ICT Degree Programme has seven different major options; this paper focuses on Health Technology. In Health Technology, a significant curriculum change in 2014 enabled transition from fragmented curriculum including dozens of courses to a new integrated curriculum built around three 30 ECTS themes. This paper focuses especially on the second theme called Customer Oriented Software Applications. From students’ point of view, the goal of this theme is to get familiar with existing health related ICT solutions and systems, understand business around health technology, recognize social and healthcare operating principles and services, and identify customers and users and their special needs and perspectives. This also acts as a background for health related web application development. Built web application is tested, developed and evaluated with real users utilizing versatile user centred development methods. This paper presents experiences obtained from the first implementation of Customer Oriented Software Applications theme. Student feedback was gathered with two questionnaires, one in the middle of the theme and other at the end of the theme. Questionnaires had qualitative and quantitative parts. Similar questionnaire was implemented in the first theme; this paper evaluates how the theme-based integrated curriculum has progressed in Health Technology major by comparing results between theme 1 and 2. In general, students were satisfied for the implementation, timing and synchronization of the courses, and the amount of work. However there is still room for development. Student feedback and teachers’ observations have been and will be used to develop the content and operating principles of the themes and whole curriculum.

Keywords: engineering education, integrated curriculum, learning and teaching methods, learning experience

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Authors: Yi-Hsiang Pan, Chen-Hui Huang, Wei-Ting Hsu

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The purposes of the study were to understand these topics as follows: 1. To explore the effect of merging teaching personal and social responsibility (TPSR) with sports education model on students' game performance and responsibility. 2. To explore the effect of sports education model on students' game performance and responsibility. 3. To compare the difference between "merging TPSR with sports education model" and "sports education model" on students' game performance and responsibility. The participants include three high school physical education teachers and six physical education classes. Every teacher teaches an experimental group and a control group. The participants had 121 students, including 65 students in the experimental group and 56 students in the control group. The research methods had game performance assessment, questionnaire investigation, interview, focus group meeting. The research instruments include personal and social responsibility questionnaire and game performance assessment instrument. Paired t-test test and MANCOVA were used to test the difference between "merging TPSR with sports education model" and "sports education model" on students' learning performance. 1) "Merging TPSR with sports education model" showed significant improvements in students' game performance, and responsibilities with self-direction, helping others, cooperation. 2) "Sports education model" also had significant improvements in students' game performance, and responsibilities with effort, self-direction, helping others. 3.) There was no significant difference in game performance and responsibilities between "merging TPSR with sports education model" and "sports education model". 4)."Merging TPSR with sports education model" significantly improve learning atmosphere and peer relationships, it may be developed in the physical education curriculum. The conclusions were as follows: Both "Merging TPSR with sports education model" and "sports education model" can help improve students' responsibility and game performance. However, "Merging TPSR with sports education model" can reduce the competitive atmosphere in highly intensive games between students. The curricular projects of hybrid TPSR-Sport Education model is a good approach for moral character education.

Keywords: curriculum and teaching model, sports self-efficacy, sport enthusiastic, character education

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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Authors: Tomasz Zarebski

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A very important element of the education system is its evaluation procedure. Each education system should be systematically evaluated and improved. Among the criteria subject to evaluation, attention should be paid to the following: structure of the study programme, implementation of the study programme, admission to studies, verification of learning outcomes achievement by students, giving credit for individual semesters and years, and awarding diplomas, competence, experience, qualifications and the number of staff providing education, staff development, and in-service training, education infrastructure, cooperation with social and economic stakeholders on the development, conditions for and methods of improving the internationalisation of education provided as part of the degree programme, supporting learning, social, academic or professional development of students and their entry on the labour market, public access to information about the study programme and quality assurance policy. Concerning the assessment process and the individual assessment indicators, the participation of students in these processes is essential. The purpose of this paper is to analyse the rules of student participation in accreditation processes on the example of individual countries in Europe. The rules of students' participation in the work of accreditation committees and their influence on the final grade of the committee were analysed. Most of the higher education institutions follow similar rules for accreditation. The general model gives the individual institution freedom to organize its own quality assurance, as long as the system lives up to the criteria for quality and relevance laid down in the particular provisions. This point also applies to students. The regulations of the following countries were examined in the legal-comparative aspect: Poland (Polish Accreditation Committee), Denmark (The Danish Accreditation Institution), France (High Council for the Evaluation of Research and Higher Education), Germany (Agency for Quality Assurance through Accreditation of Study Programmes) and Italy (National Agency for the Evaluation of Universities and Research Institutes).

Keywords: accreditation, student, study programme, quality assurance in higher education

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Authors: Yaolin Tian, Shanxiong Chen, Fujia Zhao, Xiaoyu Lin, Hailing Xiong

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Ancient books are significant culture inheritors and their background textures convey the potential history information. However, multi-style texture recovery of ancient books has received little attention. Restricted by insufficient ancient textures and complex handling process, the generation of ancient textures confronts with new challenges. For instance, training without sufficient data usually brings about overfitting or mode collapse, so some of the outputs are prone to be fake. Recently, image generation and style transfer based on deep learning are widely applied in computer vision. Breakthroughs within the field make it possible to conduct research upon multi-style texture recovery of ancient books. Under the circumstances, we proposed a network of layout analysis and image fusion system. Firstly, we trained models by using Deep Convolution Generative against Networks (DCGAN) to synthesize multi-style ancient textures; then, we analyzed layouts based on the Position Rearrangement (PR) algorithm that we proposed to adjust the layout structure of foreground content; at last, we realized our goal by fusing rearranged foreground texts and generated background. In experiments, diversified samples such as ancient Yi, Jurchen, Seal were selected as our training sets. Then, the performances of different fine-turning models were gradually improved by adjusting DCGAN model in parameters as well as structures. In order to evaluate the results scientifically, cross entropy loss function and Fréchet Inception Distance (FID) are selected to be our assessment criteria. Eventually, we got model M8 with lowest FID score. Compared with DCGAN model proposed by Radford at el., the FID score of M8 improved by 19.26%, enhancing the quality of the synthetic images profoundly.

Keywords: deep learning, image fusion, image generation, layout analysis

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Authors: Marc Toutain, Pascale Leconte, Antoine Gauthier

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Introduction: Eating Disorders (ED), such as anorexia, bulimia, and binge eating, are psychiatric illnesses that mostly affect young people. The main symptoms concern eating (restriction, excessive food intake) and weight control behaviors (laxatives, vomiting). Psychological comorbidities (depression, executive function disorders, etc.) and problematic behaviors toward physical activity (PA) are commonly associated with ED. Acquaintances on ED risk factors are still lacking, and more community sample studies are needed to improve prevention and early detection. To our knowledge, studies are needed to specifically investigate the link between ED risk level, PA, and psychological risk factors in a community sample of adolescents. The aim of this study is to assess the relation between ED risk level, exercise (type, frequency, and motivations for engaging in exercise), and psychological factors based on the Jacobi risk factors model. We suppose that a high risk of ED will be associated with the practice of high caloric cost PA, motivations oriented to weight and shape control, and psychological disturbances. Method: An online survey destined for students has been sent to several middle schools and colleges in northwest France. This survey combined several questionnaires, the Eating Attitude Test-26 assessing ED risk; the Exercise Motivation Inventory–2 assessing motivations toward PA; the Hospital Anxiety and Depression Scale assessing anxiety and depression, the Contour Drawing Rating Scale; and the Body Esteem Scale assessing body dissatisfaction, Rosenberg Self-esteem Scale assessing self-esteem, the Exercise Dependence Scale-Revised assessing PA dependence, the Multidimensional Assessment of Interoceptive Awareness assessing interoceptive awareness and the Frost Multidimensional Perfectionism Scale assessing perfectionism. Machine learning analysis will be performed in order to constitute groups with a tree-based model clustering method, extract risk profile(s) with a bootstrap method comparison, and predict ED risk with a prediction method based on a decision tree-based model. Expected results: 1044 complete records have already been collected, and the survey will be closed at the end of May 2022. Records will be analyzed with a clustering method and a bootstrap method in order to reveal risk profile(s). Furthermore, a predictive tree decision method will be done to extract an accurate predictive model of ED risk. This analysis will confirm typical main risk factors and will give more data on presumed strong risk factors such as exercise motivations and interoceptive deficit. Furthermore, it will enlighten particular risk profiles with a strong level of proof and greatly contribute to improving the early detection of ED and contribute to a better understanding of ED risk factors.

Keywords: eating disorders, risk factors, physical activity, machine learning

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Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Kathleen L. Seifert

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Students with special needs are expected to achieve the same academic standards as their general education peers, yet many students with special needs are pulled-out of general content instruction. Because of this, many students with special needs are denied content knowledge from a content expert and instead receive content instruction in a more restrictive setting. Collaborative teaching, where a general education and special education teacher work alongside each other in the same classroom, has become increasingly popular as a means to meet the diverse needs of students in America’s public schools. The idea behind co-teaching is noble; to ensure students with special needs receive content area instruction from a content expert while also receiving the necessary supports to be successful. However, in spite of this noble effort, the effects of co-teaching are not always positive. The reasons why have produced several hypotheses, one of which has to do with lack of proper training and implementation of effective evidence-based co-teaching practices. In order to examine the effects of co-teacher training, eleven teaching pairs from a small mid-western school district in the United States participated in a study. The purpose of the study was to examine the effects of co-teacher training on middle and high school student achievement in Math and Language Arts. A local university instructor provided teachers with training in co-teaching via a three-day workshop. In addition, co-teaching pairs were given the opportunity for direct observation and feedback using the Co-teaching Core Competencies Observation Checklist throughout the academic year. Data are in the process of being collected on both the students enrolled in the co-taught classes as well as on the teachers themselves. Student data compared achievement on standardized assessments and classroom performance across three domains: 1. General education students compared to students with special needs in co-taught classrooms, 2. Students with special needs in classrooms with and without co-teaching, 3. Students in classrooms where teachers were given observation and feedback compared to teachers who refused the observation and feedback. Teacher data compared the perceptions of the co-teaching initiative between teacher pairs who received direct observation and feedback from those who did not. The findings from the study will be shared with the school district and used for program improvement.

Keywords: collabortive teaching, collaboration, co-teaching, professional development

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Authors: Kishor Chandra Kandpal, Amit Kumar

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The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

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Authors: Taibat Busari

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Electronic media has created new options for enhancing education. It has long been providing innovative methods for arousing students’ attention in learning and improves teachers’ performance in disseminating instructional contents. However, the advancement of electronic media has increased the flexibility, availability, accessibility and improved communications among students-students, students-teacher, and teacher-students. This study investigated: (i) teachers’ accessibility to, and utilization of electronic media for teaching basic science and technology in Ilorin metropolis; (ii) the influence of school proprietorship on teachers’ access to and utilization of electronic media for teaching and; the influence of teachers’ gender on the use of electronic media. The research was a descriptive design using the survey method. The study sample was drawn for private and public secondary schools in Ilorin Metropolis. The respondents were 285 basic science and technology teachers, which comprised of 146 males and 139 females. A structured researcher designed questionnaire was used to gather data for the study. Pilot study was carried out on mini sample of 20 basic science and technology teachers in five schools which are not part of the study’s population. It was then subjected to Cronbach’s Alpha and yielded the values 0.794 for availability, 0.730 for accessibility and 0.84 for utilization of electronic media. The research questions were answered using mean and percentage while research hypotheses one and two was tested using t- test. The findings of the study showed that: (i) electronic media are available for teaching basic science and technology; (ii) teachers’ had access to electronic media for teaching; (iii) teachers’ utilized electronic media for teaching basic science and technology; (iv) there was no significant difference between teachers’ utilization of electronic media for teaching; (v) there was no significant difference between teachers’ utilization of electronic media for teaching based on school proprietorship. The study, therefore, concluded that teachers’ had access to electronic media and utilized it for teaching purposes. Gender had no influence on teachers’ access to and utilization on electronic media for teaching and also, school proprietorship had no influence on access and utilization of electronic media for teaching. Based on findings it was recommended that electronic media should be made available and utilized in all schools across the nation to improve the learning rate of the students.

Keywords: electronic media, basic science and technology, teachers' accessibility, Nigeria

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Authors: Natacha Jesus-Silva, Carla S. Pereira, Natercia Durao, Maria Das Dores Formosinho, Cristina Costa-Lobo

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Any assessment process, by its very nature, raises a wide range of doubts, uncertainties, and insecurities of all kinds. The evaluation process should be ethically irreproachable, treating each and every one of the evaluated according to a conduct that ensures that the process is fair, contributing to all recognize and feel well with the processes and results of the evaluation. This is a very important starting point and implies that positive and constructive conceptions and attitudes are developed regarding the evaluation of teaching performance, where students' responsibility is desired. It is not uncommon to find teachers feeling threatened at various levels, in particular as regards their autonomy and their professional dignity. Evaluation must be useful in that it should enable decisions to be taken to improve teacher performance, the quality of teaching or the learning climate of the school. This study is part of a research project whose main objective is to identify, select, evaluate and synthesize the available evidence on Quality Indicators in Higher Education. In this work, the 01 parameters resulting from pedagogical surveys in a Portuguese higher education institution in the north of the country will be presented, surveys for the 2015/2016 school year, presented to 1751 students, in a total of 11 degrees and 18 master's degrees. It has analyzed the evaluation made by students with respect to the performance of a group of 68 teachers working full time. This paper presents the lessons learned in the last three academic years, allowing for the identification of the effects on the following areas: teaching strategies and methodologies, capacity of systematization, learning climate, creation of conditions for active student participation. This paper describes the procedures resulting from the descriptive analysis (frequency analysis, descriptive measures and association measures) and inferential analysis (ANOVA one-way, MANOVA one-way, MANOVA two-way and correlation analysis).

Keywords: teaching performance, higher education, students responsibility, indicators of teaching management

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Authors: Luke Taylor, Samantha J. Hall, Kenneth I. Cumming, Jakki Bardsley, Scott S. P. Wildman

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Medway School of Pharmacy, as part of an Equality Diversity and Inclusivity (EDI) initiative run by the University of Kent, decided to take steps to try and negate disparities in numeracy competencies within students undertaking the Master of Pharmacy degree in order to combat a trend in pharmacy students’ numerical abilities upon entry. This included a research driven project 1) to identify if pharmacy students are aware of weaknesses in their numeracy capabilities, and 2) recognise where their numeracy skillset is lacking. In addition to gaining this student perspective, a number of actions have been implemented to support students in improving their numeracy competencies. Reflective and quantitative analysis has shown promising improvements for the final year cohort of 2014/15 when compared to previous years. The method of involving student feedback into the structure of numeracy teaching/support has proven to be extremely beneficial to both students and teaching staff alike. Students have felt empowered and in control of their own learning requirements, leading to increased engagement and attainment. School teaching staff have received quality data to help improve existing initiatives and to innovate further in the area of numeracy teaching. In light of the recognised improvements, further actions are currently being trialled in the area of numeracy support. This involves utilising Virtual Learning Environment platforms to provide individualised support as a supplement to the increased numeracy mentoring (staff and peer) provided to students. Mentors who provide group or one-to-one sessions are now given significant levels of training in dealing with situations that commonly arise from mentoring schemes. They are also provided with continued support throughout the life of their degree. Following results from this study, Medway School of Pharmacy hopes to drive increasing numeracy standards within Pharmacy (primarily through championing peer mentoring) as well as other healthcare professions including Midwifery and Nursing.

Keywords: attainment, ethnicity, numeracy, pharmacy, support

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Authors: Kevin Wang, Jian Ge, Yinan Zhao, Kevin Willis

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Kepler has discovered over 4000 exoplanets and candidates. However, current transit planet detection techniques based on the wavelet analysis and the Box Least Squares (BLS) algorithm have limited sensitivity in detecting minor planets with a low signal-to-noise ratio (SNR) and long periods with only 3-4 repeated signals over the mission lifetime of 4 years. This paper presents a novel precise-period transit signal detection methodology based on a new Graphics Processing Unit (GPU) Fast Folding algorithm in conjunction with a Convolutional Neural Network (CNN) to detect low SNR and/or long-period transit planet signals. A comparison with BLS is conducted on both simulated light curves and real data, demonstrating that the new method has higher speed, sensitivity, and reliability. For instance, the new system can detect transits with SNR as low as three while the performance of BLS drops off quickly around SNR of 7. Meanwhile, the GPU Fast Folding method folds light curves 25 times faster than BLS, a significant gain that allows exoplanet detection to occur at unprecedented period precision. This new method has been tested with all known transit signals with 100% confirmation. In addition, this new method has been successfully applied to the Kepler of Interest (KOI) data and identified a few new Earth-sized Ultra-short period (USP) exoplanet candidates and habitable planet candidates. The results highlight the promise for GPU Fast Folding as a replacement to the traditional BLS algorithm for finding small and/or long-period habitable and Earth-sized planet candidates in-transit data taken with Kepler and other space transit missions such as TESS(Transiting Exoplanet Survey Satellite) and PLATO(PLAnetary Transits and Oscillations of stars).

Keywords: algorithms, astronomy data analysis, deep learning, exoplanet detection methods, small planets, habitable planets, transit photometry

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Authors: V. Nalina, P. Jayarekha

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Consultancy by an engineering faculty member of an institution undertakes consulting assignments to provide professional or technical solutions to specific fields. Consulting is providing an opportunity for the engineering faculty to share their insights for the real world problems. It is a dynamic learning process with respect to students and faculty as it increases the teaching and research activities. In this paper, we discuss the need for consultancy in engineering education with faculty contribution towards consultancy and advantages of consultancy to institutions. Balance the workload of the faculty consulting with the responsibilities of academics defined by the universities.

Keywords: consultancy, academic consulting, engineering consultancy, faculty consulting

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: Line Massé, Claire Baudry, Claudia Verret, Marie-France Nadeau, Anne Brault-Labbé

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Little research has been conducted on educational services adapted for twice exceptional students. Within an action research, a cluster grouping was set up in an elementary school in Quebec, bringing together gifted or doubly exceptional (2E) students (n = 11) and students not identified as gifted (n = 8) within a multilevel class (3ᵣ𝒹 and 4ₜₕ years). 2E students had either attention deficit hyperactivity disorder (n = 8, including 3 with specific learning disability) or autism spectrum disorder (n = 2). Differentiated instructions strategies were implemented, including the possibility of progressing at their own pace of learning, independent study or research projects, flexible accommodation, tutoring with older students and the development of socio-emotional learning. A specialized educator also supported the teacher in the class for behavioural and socio-affective aspects. Objectives: The study aimed to assess the impacts of the grouping on all students, their academic motivation, and their socio-emotional adaptation. Method: A mixed method was used, combining a qualitative approach with a quantitative approach. Semi-directed interviews were conducted with students (N = 18, 4 girls and 14 boys aged 8 to 9) and one of their parents (N = 18) at the end of the school year. Parents and students completed two questionnaires at the beginning and end of the school year: the Behavior Assessment System for Children-3, children or parents versions (BASC-3, Reynolds and Kampus, 2015) and the Academic Motivation in Education (Vallerand et al., 1993). Parents also completed the Multidimensional Student Life Satisfaction Scale (Huebner, 1994, adapted by Fenouillet et al., 2014) comprising three domains (school, friendships, and motivation). Mixed thematic analyzes were carried out on the data from the interviews using the N'Vivo software. Related-samples Wilcoxon rank-sums tests were conducted for the data from the questionnaires. Results: Different themes emerge from the students' comments, including a positive impact on school motivation or attitude toward school, improved school results, reduction of their behavioural difficulties and improvement of their social relations. These remarks were more frequent among 2E students. Most 2E students also noted an improvement in their academic performance. Most parents reported improvements in attitudes toward school and reductions in disruptive behaviours in the classroom. Some parents also observed changes in behaviours at home or in the socio-emotional well-being of their children, here again, particularly parents of 2E children. Analysis of questionnaires revealed significant differences at the end of the school year, more specifically pertaining to extrinsic motivation identified, problems of conduct, attention, emotional self-control, executive functioning, negative emotions, functional deficiencies, and satisfaction regarding friendships. These results indicate that this approach could benefit not only gifted and doubly exceptional students but also students not identified as gifted.

Keywords: Cluster grouping, elementary school, giftedness, mixed methods, twice exceptional students

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Authors: Joseph Bertrand Iboum Kissaaka, Charles Fonyuy Ngum Tchioben, Paul Gustave Fowe Kwetche, Jeannette Ngo Elogan Ntem, Joseph Binyet Njebakal, Ribert Yvan Makosso-Tchapi, François Mvondo Owono, Marie Joseph Ntamak-Nida

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Located in the Gulf of Guinea, the Kribi-Campo sub-basin belongs to the Aptian salt basins along the West African Margin. In this paper, we investigated the tectono-stratigraphic architecture of the basin, focusing on the role of salt tectonics and strike-slip faults along the Kribi Fracture Zone with implications for reservoir prediction. Using 2D seismic data and well data interpreted through sequence stratigraphy with integrated seismic attributes analysis with Python Programming and unsupervised Machine Learning, at least six second-order sequences, indicating three main stages of tectono-stratigraphic evolution, were determined: pre-salt syn-rift, post-salt rift climax and post-rift stages. The pre-salt syn-rift stage with KTS1 tectonosequence (Barremian-Aptian) reveals a transform rifting along NE-SW transfer faults associated with N-S to NNE-SSW syn-rift longitudinal faults bounding a NW-SE half-graben filled with alluvial to lacustrine-fan delta deposits. The post-salt rift-climax stage (Lower to Upper Cretaceous) includes two second-order tectonosequences (KTS2 and KTS3) associated with the salt tectonics and Campo High uplift. During the rift-climax stage, the growth of salt diapirs developed syncline withdrawal basins filled by early forced regression, mid transgressive and late normal regressive systems tracts. The early rift climax underlines some fine-grained hangingwall fans or delta deposits and coarse-grained fans from the footwall of fault scarps. The post-rift stage (Paleogene to Neogene) contains at least three main tectonosequences KTS4, KTS5 and KTS6-7. The first one developed some turbiditic lobe complexes considered as mass transport complexes and feeder channel-lobe complexes cutting the unstable shelf edge of the Campo High. The last two developed submarine Channel Complexes associated with lobes towards the southern part and braided delta to tidal channels towards the northern part of the Kribi-Campo sub-basin. The reservoir distribution in the Kribi-Campo sub-basin reveals some channels, fan lobes reservoirs and stacked channels reaching up to the polygonal fault systems.

Keywords: tectono-stratigraphic architecture, Kribi-Campo sub-basin, machine learning, pre-salt sequences, post-salt sequences

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Authors: Rebecca Lees, Deborah Anderson

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Whilst the majority of research into social media in education focuses on the applications for teaching and learning environments, this study looks at how such activities can be managed by investigating the current state of social media regulation within UK higher education. Social media has pervaded almost all aspects of higher education; from marketing, recruitment and alumni relations to both distance and classroom-based learning and teaching activities. In terms of who uses it and how it is used, social media is growing at an unprecedented rate, particularly amongst the target market for higher education. Whilst the platform presents opportunities not found in more traditional methods of communication and interaction, such as speed and reach, it also carries substantial risks that come with inappropriate use, lack of control and issues of privacy. Typically, organisations rely on the concept of a social contract to guide employee behaviour to conform to the expectations of that organisation. Yet, where academia and social media intersect applying the notion of a social contract to enforce governance may be problematic; firstly considering the emphasis on treating students as customers with a growing focus on the use and collection of satisfaction metrics; and secondly regarding the notion of academic’s freedom of speech, opinion and discussion, which is a long-held tradition of learning instruction. Therefore the need for sound governance procedures to support expectations over online behaviour is vital, especially when the speed and breadth of adoption of social media activities has in the past outrun organisations’ abilities to manage it. An analysis of the current level of governance was conducted by gathering relevant policies, guidelines and best practice documentation available online via internet search and institutional requests. The documents were then subjected to a content analysis in the second phase of this study to determine the approach taken by institutions to apply such governance. Documentation was separated according to audience, i.e.: applicable to staff, students or all users. Given many of these included guests and visitors to the institution within their scope being easily accessible was considered important. Yet, within the UK only about half of all education institutions had explicit social media governance documentation available online without requiring member access or considerable searching. Where they existed, the majority focused solely on employee activities and tended to be policy based rather than rooted in guidelines or best practices, or held a fallback position of governing online behaviour via implicit instructions within IT and computer regulations. Explicit instructions over expected online behaviours is therefore lacking within UK HE. Given the number of educational practices that now include significant online components, it is imperative that education organisations keep up to date with the progress of social media use. Initial results from the second phase of this study which analyses the content of the governance documentation suggests they require reading levels at or above the target audience, with some considerable variability in length and layout. Further analysis will add to this growing field of investigating social media governance within higher education.

Keywords: governance, higher education, policy, social media

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Authors: Shan Wang, Fahad Alhathal, Daniel Hobson

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User-centered design skills play an important role in crafting a positive and intuitive user experience for software applications. Embracing a user-centric design approach involves understanding the needs, preferences, and behaviors of the end-users throughout the design process. This mindset not only enhances the usability of the software but also fosters a deeper connection between the digital product and its users. This paper encompasses a 6-month knowledge exchange collaboration project between an academic institution and an external industry in 2023, aims to improve the user experience of a digital platform utilized for a knowledge management tool, to understand users' preferences for features, identify sources of frustration, and pinpoint areas for enhancement. This research conducted one of the most effective methods to implement user-centered design through co-design workshops for testing user onboarding experiences that involve the active participation of users in the design process. More specifically, in January 2023, we organized eight workshops with a diverse group of 11 individuals. Throughout these sessions, we accumulated a total of 11 hours of qualitative data in both video and audio formats. Subsequently, we conducted an analysis of user journeys, identifying common issues and potential areas for improvement. This analysis was pivotal in guiding the knowledge management software in prioritizing feature enhancements and design improvements. Employing a user-centered design thinking process, we developed a series of graphic design solutions in collaboration with the software management tool company. These solutions were targeted at refining onboarding user experiences, workplace interfaces, and interactive design. Some of these design solutions were translated into tangible interfaces for the knowledge management tool. By actively involving users in the design process and valuing their input, developers can create products that are not only functional but also resonate with the end-users, ultimately leading to greater success in the competitive software landscape. In conclusion, this paper not only contributes insights into designing onboarding user experiences for software within a co-design approach but also presents key theories on leveraging the user-centered design process in software design to enhance overall user experiences.

Keywords: user experiences, co-design, design process, knowledge management tool, user-centered design

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Authors: Cherres Sara, Cajas Diego

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This paper explores how EFL teachers understand the process of Lesson Study in Ecuadorian schools and the challenges and opportunities that it brings to the improvement of their teaching practice. Using a narrative research methodology, this study presents the results of the application of the four steps of Lesson Study carried out by seven teachers in four different schools located in the Southern part of Ecuador during four months. Before starting the implementation of the lesson study, 30 teachers were trained on this model. This training was opened to EFL teachers working in public and private schools without any charge. The criteria to select these teachers were first, to be minimum a one-year in-service teacher, second, to have a b2 level of English, and third, to be able to commit to follow the course guidelines. After the course, seven teachers decided to continue with the implementation of the Lesson Study in their respective institutions. During the implementation of the Lesson Study, data was collected through observations, in-depth interviews and teachers’ planning meetings; and analyzed using a thematic analysis. The results of this study are presented using the lenses of seven EFL teachers that explained the challenges and opportunities that the implementation of Lesson Study conveyed. The challenges identified were the limited capacity of reflection and recognition of the activities that required improvement after the class, limited capacity to provide truthful peer feedback, teachers wrong notions about their performance in their classes, difficulties to follow a collaborative lesson plan; and, the disconnection between class activities and the class content. The opportunities identified were teachers’ predisposition to collaborate, teachers’ disposition to attend professional development courses, their commitment to work extra hours in planning meetings, their openness and their desired to be observed in their classes; and, their willingness to share class materials and knowledge. On the other hand, the results show that there is a disconnection between teachers’ knowledge of ELT and its proper application in class (from theory to practice). There are also, rigid institutional conceptions of teaching that do not allow teaching innovations. The authors concluded that there is a disconnection between teachers’ knowledge of ELT and its proper application in class (from theory to practice). There are also, rigid institutional conceptions of teaching that do not allow teaching innovations for example: excessive institutional paperwork and activities that are not connected to the development of students’ competences.

Keywords: ELT, lesson study, teachers’ professional development, teachers’ collaboration

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Authors: Daly M. J, Condron C, Mulhall C, Eppich W, O'Neill J.

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Introduction: In contemporary clinical cardiology, comprehensive and holistic bedside evaluation including accurate cardiac auscultation is in decline despite having positive effects on patients and their outcomes. Methods: Scripted histories and scoring checklists for three clinical scenarios in cardiology were co-created and refined through iterative consensus by a panel of clinical experts; these were then paired with recordings of auscultatory findings from three actual patients with known valvular heart disease. A wearable vest with embedded pressure-sensitive panel speakers was developed to transmit these recordings when examined at the standard auscultation points. RCSI medical students volunteered for a series of three formative long case examinations in cardiology (LC1 – LC3) using this hybrid simulation. Participants were randomised into two groups: Group 1 received individual teaching from an expert trainer between LC1 and LC2; Group 2 received the same intervention between LC2 and LC3. Each participant’s long case examination performance was recorded and blindly scored by two peer participants and two RCSI examiners. Results: Sixty-eight participants were included in the study (age 27.6 ± 0.1 years; 74% female) and randomised into two groups; there were no significant differences in baseline characteristics between groups. Overall, the median total faculty examiner score was 39.8% (35.8 – 44.6%) in LC1 and increased to 63.3% (56.9 – 66.4%) in LC3, with those in Group 1 showing a greater improvement in LC2 total score than that observed in Group 2 (p < .001). Using the novel checklist, intraclass correlation coefficients (ICC) were excellent between examiners in all cases: ICC .994 – .997 (p < .001); correlation between peers and examiners improved in LC2 following peer grading of LC1 performances: ICC .857 – .867 (p < .001). Conclusion: Hybrid simulation and quantitative grading improve learning, standardisation of assessment, and direct comparisons of both performance and acumen in clinical cardiology.

Keywords: cardiology, clinical skills, long case examination, hybrid simulation, checklist

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Authors: Simon Winberg

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The landscape of professional postgraduate education is changing: the focus of these programmes is moving from preparing candidates for a life in academia towards a focus of training in expert knowledge and skills to support industry. This is especially pronounced in engineering disciplines where increasingly more complex products are drawing on a depth of knowledge from multiple fields. This connects strongly with the broader notion of Industry 4.0 – where technology and society are being brought together to achieve more powerful and desirable products, but products whose inner workings also are more complex than before. The changes in what we do, and how we do it, has a profound impact on what industry would like universities to provide. One such change is the increased demand for taught doctoral and Masters programmes. These programmes aim to provide skills and training for professionals, to expand their knowledge of state-of-the-art tools and technologies. This paper investigates one such course, namely a Software Defined Radio (SDR) Master’s degree course. The teaching support for this course had to be drawn from an existing pool of academics, none of who were specialists in this field. The paper focuses on the kind of educator, a ‘hybrid academic’, assembled from available academic staff and bolstered by research. The conceptual framework for this paper combines Activity Theory and Genre Ecology. Activity Theory is used to reason about learning and interactions during the course, and Genre Ecology is used to model building and sharing of technical knowledge related to using tools and artifacts. Data were obtained from meetings with students and lecturers, logs, project reports, and course evaluations. The findings show how the course, which was initially academically-oriented, metamorphosed into a tool-dominant peer-learning structure, largely supported by the sharing of technical tool-based knowledge. While the academic staff could address gaps in the participants’ fundamental knowledge of radio systems, the participants brought with them extensive specialized knowledge and tool experience which they shared with the class. This created a complicated dynamic in the class, which centered largely on engagements with technology artifacts, such as simulators, from which knowledge was built. The course was characterized by a richness of ‘epistemic objects’, which is to say objects that had knowledge-generating qualities. A significant portion of the course curriculum had to be adapted, and the learning methods changed to accommodate the dynamic interactions that occurred during classes. This paper explains the SDR Masters course in terms of conflicts and innovations in its activity system, as well as the continually hybridizing genre ecology to show how the structuring and resource-dependence of the course transformed from its initial ‘traditional’ academic structure to a more entangled arrangement over time. It is hoped that insights from this paper would benefit other educators involved in the design and teaching of similar types of specialized professional postgraduate taught programmes.

Keywords: professional postgraduate education, taught masters, engineering education, software defined radio

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Authors: Dona Abdulwassi, Dhaee Dahlawi, Yara Zainy, Leen Joharji

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The relationship between Netflix and artificial intelligence is discussed in this paper. Netflix uses the most effective and efficient approaches to apply artificial intelligence, machine learning, and data science. Netflix employs the personalization tool for their users, recommending or suggesting shows based on what those users have already watched. The researchers conducted an experiment to learn more about how Netflix is used and how AI affects the user experience. The main conclusions of this study are that Netflix has a wide range of AI features, most users are happy with their Netflix subscriptions, and the majority prefer Netflix to alternative apps.

Keywords: easy accessibility, recommends, accuracy, privacy

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Authors: Beazidou Eleftheria

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Roma children face discrimination in schools where they are the minority. On the other hand, teachers do not identify the specific needs of Roma students for educational and social inclusion and generally use a very restricted repertoire of insufficient strategies for helping them. Modern classrooms can and should look different. Therefore, engaging in transformational learning with young children is a deliberate choice. Transformation implies a different way of thinking and acting. This requires new knowledge that incorporates multiple perspectives and actions in order to generate experiences for further learning. In this way, we build knowledge based on empirical examples, and we share what works efficiently. The present research aims at assisting the participating teachers to improve their teaching inclusive practice, thus ultimately benefiting their students. To increase the impact of transformative efforts with a ‘new’ teaching approach, we implemented a classroom-based action research program for over six months in five kindergarten classrooms with Roma and non-Roma students. More specifically, we explore a) information about participants’ experience of the program and b) if the program is successful in helping participants to change their teaching practice. Action research is, by definition, a form of inquiry that is intended to have both action and research outcomes. The action research process that we followed included five phases: 1. Defining the problem: As teachers said, the Roma students are often the most excluded group in schools (Low social interaction and participation in classroom activities) 2. Developing a plan to address the problem: We decided to address the problem by improving/transforming the inclusive practices that teachers implemented in their classrooms. 3. Acting: implementing the plan: We incorporated new activities for all students with the goals: a) All students being passionate about their learning, b) Teachers must investigate issues in the educational context that are personal and meaningful to children's growth, c) Establishment of a new module for values and skills for all students, d) Raising awareness in culture of Roma, e) Teaching students to reflect. 4. Observing: We explore the potential for transformation in the action research program that involves observations of students’ participation in classroom activities and peer interaction. – thus, generated evidence from data. 5. Reflecting and acting: After analyzing and evaluating the outcomes from data and considering the obstacles during the program’s implementation, we established new goals for the next steps of the program. These are centered in: a) the literacy skills of Roma students and b) the transformation of teacher’s perceptions and believes, which have a powerful impact on their willingness to adopt new teaching strategies. The final evaluation of the program showed a significant achievement of the transformative goals, which were related to the active participation of the Roma students in classroom activities and peer interaction, while the activities which were related to literacy skills did not have the expected results. In conclusion, children were equipped with relevant knowledge and skills to raise their potential and contribute to wider societal development as well as teachers improved their teaching inclusive practice.

Keywords: action research, inclusive practices, kindergarten, transformation

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Authors: Bianca Maria Rulli, Lenny Valentino Schiaretti

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The considerable recent urbanization has increasingly sharpened environmental and social problems all over the world. During the recent years, many answers to the alarming attitudes in modern cities have emerged: a drastic reduction in the rate of growth is becoming essential for future generations and small scale economies are considered more adaptive and sustainable. According to the concept of degrowth, cities should consider surpassing the centralization of urban living by redefining the relationship between rural and urban knowledge; growing food in cities fundamentally contributes to the increase of social and ecological resilience. Through an innovative approach, this research combines the benefits of urban agriculture (increase of biological diversity, shorter and thus more efficient supply chains, food security) and temporary land use. They stimulate collaborative practices to satisfy the changing needs of communities and stakeholders. The concept proposes a coherent strategy to create a sustainable development of urban spaces, introducing a productive green-network to link specific areas in the city. By shifting the current relationship between architecture and landscape, the former process of ground consumption is deeply revised. Temporary modules can be used as concrete tools to create temporal areas of innovation, transforming vacant or marginal spaces into potential laboratories for the development of the city. The only permanent ground traces, such as foundations, are minimized in order to allow future land re-use. The aim is to describe a new mindset regarding the quality of space in the metropolis which allows, in a completely flexible way, to bring back the green and the urban farming into the cities. The wide possibilities of the research are analyzed in two different case-studies. The first is a regeneration/connection project designated for social housing, the second concerns the use of temporary modules to answer to the potential needs of social structures. The intention of the productive green-network is to link the different vacant spaces to each other as well as to the entire urban fabric. This also generates a potential improvement of the current situation of underprivileged and disadvantaged persons.

Keywords: degrowth, green network, land use, temporary building, urban farming

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Authors: Gift Chidi-Onwuta, Iwe Nkem Nkechinyere, Chikamadu Christabelle Chinyere

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The teaching of English is a resource-driven activity that requires rich resource-classroom settings for the delivery of effective lessons and the acquisition of interpersonal skills for integration in a target-language environment. However, throughout the world, English is often taught in low-resource classrooms. This paper is aimed to reveal the common problems associated with teaching English in low-resource environments and the prospects for teachers who found themselves in such undefined teaching settings. Self-structured and validated questionnaire in a closed-ended format, open question format and scaling format was administered to teachers across five countries: Nigeria, Cameroun, Iraq, Turkey, and Sudan. The study adopts situational language teaching theory (SLTT), which emphasizes a performance improvement imperative. This study inclines to this model because it maintains that learning must be fun and enjoyable like playing a favorite sport, just as in real life. Since teaching resources make learning engaging, we found this model apt for the current study. The perceptions of teachers about accessibility and functionality of teaching material resources, the nature of teaching outcomes in resource-less environments, their levels of involvement in improvisation and the prospects associated with resource limitations were sourced. Data were analysed using percentages and presented in frequency tables. Results: showed that a greater number of teachers across these nations do not have access to sufficient productive resource materials that can aid effective English language teaching. Teaching outcomes, from the findings, are affected by low material resources; however, results show certain advantages to teaching English with limited resources: flexibility and autonomy with students and creativity and innovation amongst teachers. Results further revealed group work, story, critical thinking strategy, flex, cardboards and flashcards, dictation and dramatization as common teaching strategies, as well as materials adopted by teachers to overcome low resource-related challenges in classrooms.

Keywords: teaching materials, low-resource environments, English language teaching, situational language theory

Procedia PDF Downloads 115