Search results for: active learning approach

Authors: Ghazala Hcini, Imen Jdey, Hela Ltifi

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Malaria disease should be considered and handled as a potential restorative catastrophe. One of the most challenging tasks in the field of microscopy image processing is due to differences in test design and vulnerability of cell classifications. In this article, we focused on applying deep learning to classify patients by identifying images of infected and uninfected cells. We performed multiple forms, counting a classification approach using the Hue, Saturation, Value (HSV) color space. HSV is used since of its superior ability to speak to image brightness; at long last, for classification, a convolutional neural network (CNN) architecture is created. Clusters of focus were used to deliver the classification. The highlights got to be forbidden, and a few more clamor sorts are included in the information. The suggested method has a precision of 99.79%, a recall value of 99.55%, and provides 99.96% accuracy.

Keywords: deep learning, convolutional neural network, image classification, color transformation, HSV color, malaria diagnosis, malaria cells images

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Authors: Haitham Qaralleh, Syed Z. Idid, Shahbudin Saad, Deny Susanti, Osama Althunibat

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This study was carried out to isolate the active antimicrobial compounds from Neopetrosia exigua using bio-guided assay isolation against Staphylococcus aureus. N. exigua was extracted using methanol and subjected to liquid-liquid extraction using solvents with different polarity (n-hexane, carbon tetrachloride, dichloromethane, n-butanol and water). Purification of the active components of n-butanol and dichloromethane fractions was done using Sephadex LH-20 and reverse phase chromatography. Based on the biological guided fractionation results, dichloromethane and n-butanol fractions showed the highest antimicrobial activity. Purification of the active components of n-butanol and dichloromethane fractions yielded three compounds. The structure of the isolated compounds were elucidated and found to be 5-hydroxy-1H-indole-3-carboxylic acid methyl ester, cyclo-1`-demethylcystalgerone and avarol derivative. Avarol was showed potent bactericidal effect against S. aureus. N. exigua appears to be rich source of natural antimicrobial agents. Further studies are needed to investigate the mode of action of these compounds.

Keywords: antimicrobial, avarol, Neopetrosia exigua, Staphylococcus aureus

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Authors: Mahta Eskandarnejad

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The aim of this paper was to compare physical activity and mental toughness in the staff and students of the University of Tabriz. 615 people participated in this study and filled demographic questionnaire, mental thoughness48 (MTQ48) questionnaire and habitual physical activity questionnaire (Baecke physical activity questionnaire). The research sample included 355 students and 260 staff (615 questionnaires). For analyzing hypotheses MANOVA, correlation and independent t-test were used. Based on the result; some subscales of mental toughness and physical activity were significantly related. The result showed the significant correlation between mental toughness and physical activity in student and no significant correlation in staff. Students were significantly physically more active than staff, and mental toughness was higher in staff. There was no difference in mental toughness variable between active participants (active staff and student). The results of this study showed that mental toughness could influence the way a person cope with living conditions. It is expected that mental toughness changes can lead to changing in levels of physical activity. It should be noted that the other variables should not be ignored.

Keywords: Baecke physical activity questionnaire, mental toughness, physical activity, university staff, university student

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Authors: Abdullah Bal

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This paper presents a one-class classification (OCC) technique based on Fukunaga-Koontz Transform (FKT) for binary classification problems. The FKT is originally a powerful tool to feature selection and ordering for two-class problems. To utilize the standard FKT for data domain description problem (i.e., one-class classification), in this paper, a set of non-class samples which exist outside of positive class (target class) describing boundary formed with limited training data has been constructed synthetically. The tunnel-like decision boundary around upper and lower border of target class samples has been designed using statistical properties of feature vectors belonging to the training data. To capture higher order of statistics of data and increase discrimination ability, the proposed method, termed one-class FKT (OC-FKT), has been extended to its nonlinear version via kernel machines and referred as OC-KFKT for short. Multiple kernel learning (MKL) is a favorable family of machine learning such that tries to find an optimal combination of a set of sub-kernels to achieve a better result. However, the discriminative ability of some of the base kernels may be low and the OC-KFKT designed by this type of kernels leads to unsatisfactory classification performance. To address this problem, the quality of sub-kernels should be evaluated, and the weak kernels must be discarded before the final decision making process. MKL/OC-FKT and selective MKL/OC-FKT frameworks have been designed stimulated by ensemble learning (EL) to weight and then select the sub-classifiers using the discriminability and diversities measured by eigenvalue ratios. The eigenvalue ratios have been assessed based on their regions on the FKT subspaces. The comparative experiments, performed on various low and high dimensional data, against state-of-the-art algorithms confirm the effectiveness of our techniques, especially in case of small sample size (SSS) conditions.

Keywords: ensemble methods, fukunaga-koontz transform, kernel-based methods, multiple kernel learning, one-class classification

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Authors: Jingwen Ou

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Writing for academic purposes in a second or foreign language poses a significant challenge for non-native speakers, particularly at the tertiary level, where English academic writing for L2 students is often hindered by difficulties in academic discourse, including vocabulary, academic register, and organization. The past two decades have witnessed a rising popularity in the application of the data-driven learning (DDL) approach in EAP writing instruction. In light of such a trend, this study aims to enhance the integration of DDL into English for academic purposes (EAP) writing classrooms by investigating the perception of Chinese college students regarding the use of corpus tools for improving EAP writing. Additionally, the research explores their corpus consultation behaviors during training to provide insights into corpus-assisted EAP instruction for DDL practitioners. Given the uprising popularity of DDL, this research aims to investigate Chinese university students’ use of corpus tools with three main foci: 1) the influence of corpus tools on learning behaviours, 2) the influence of corpus tools on students’ academic writing performance outcomes, and 3) students’ perceptions and potential perceptional changes towards the use of such tools. Three corpus tools, CQPWeb, Sketch Engine, and LancsBox X, are selected for investigation due to the scarcity of empirical research on patterns of learners’ engagement with a combination of multiple corpora. The research adopts a pre-test / post-test design for the evaluation of students’ academic writing performance before and after the intervention. Twenty participants will be divided into two groups: an intervention and a non-intervention group. Three corpus training workshops will be delivered at the beginning, middle, and end of a semester. An online survey and three separate focus group interviews are designed to investigate students’ perceptions of the use of corpus tools for improving academic writing skills, particularly the rhetorical functions in different essay sections. Insights from students’ consultation sessions indicated difficulties with DDL practice, including insufficiency of time to complete all tasks, struggle with technical set-up, unfamiliarity with the DDL approach and difficulty with some advanced corpus functions. Findings from the main study aim to provide pedagogical insights and training resources for EAP practitioners and learners.

Keywords: corpus linguistics, data-driven learning, English for academic purposes, tertiary education in China

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Authors: Surajit Chakrabarty, Piyush Chauhan, Subhasis Panda, Sujoy Bhattacharya

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A large proportion of roads in India are not well maintained as per the laid down public safety guidelines leading to loss of direction control and fatal accidents. We propose a technique to detect speed breakers and potholes using mobile sensor data captured from multiple vehicles and provide a profile of the road. This would, in turn, help in monitoring roads and revolutionize digital maps. Incorporating randomness in the model formulation for detection of speed breakers and potholes is crucial due to substantial heterogeneity observed in data obtained using a mobile application from multiple vehicles driven by different drivers. This is accomplished with Hidden Markov Models, whose hidden state sequence is found for each time step given the observables sequence, and are then fed as input to LSTM network with peephole connections. A precision score of 0.96 and 0.63 is obtained for classifying bumps and potholes, respectively, a significant improvement from the machine learning based models. Further visualization of bumps/potholes is done by converting time series to images using Markov Transition Fields where a significant demarcation among bump/potholes is observed.

Keywords: deep learning, hidden Markov model, pothole, speed breaker

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Authors: Marzieh Yassin, Fereshteh Navaee, Javad Sarrafzadeh, Reza Salehi

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Introduction: Myofascial trigger point (MTrP) is one of the most common sources of musculoskeletal pain. Approximately 30-85% of the patients with musculoskeletal pains would experience MTrP in their life. The prevalence of MTrP has reported in the patients seen in a general orthopedic clinic, general medical clinic and specialty pain management centers, 21%, 30% and 93% respectively. Nowadays, dry needling is suggested as a standard treatment for MTrPs. The purpose of the present study was to examine the effectiveness of dry needling with stretching upper trapezius muscle on pain and pain pressure threshold in participants with active myofascial trigger point. Methods: Thirty participants with an active myofascial trigger point of the upper trapezius muscle were randomly divided into two groups: dry needling with passive stretch (n=15) and passive stretch alone (n=15). They received 5 sessions of the treatments for three weeks. The outcomes were pain intensity and pain pressure threshold that were assessed with visual analogue scale and algometer respectively. Results: Significant improvement in pain and pain pressure threshold was observed in both groups (P=0.0001) after the treatment. Also, the results showed a significant difference in measurements between two groups (P<0.05). Conclusion: Dry needling with passive stretch can be more effective on pain and pain pressure threshold than passive stretching alone in short term in participants with active myofascial trigger points.

Keywords: dry needling, myofascial pain syndrome, myofascial trigger point, stretching

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Authors: Alexandra Shipley

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Background: Undergraduate paediatric teaching must overcome two major challenges: 1) balancing patient safety with active student engagement and 2) exposing students to a comprehensive range of pathologies within a relatively short clinical placement. Whilst lectures and shadowing on paediatric wards constitute the mainstay of learning, Simulation and Virtual Reality (VR) are emerging as effective teaching tools, which - immune to the unpredictability and seasonal variation of hospital presentations - could expose students to the entire syllabus more reliably, efficiently, and independently. We aim to evaluate the potential utility of Simulation and VR in addressing gaps within the traditional paediatric curriculum from the perspective of medical students. Summary of Work: Exposure to and perceived utility of various learning opportunities within the Paediatric and Emergency Medicine courses were assessed through a questionnaire completed by 5th year medical students (n=23). Summary of Results: Students reported limited exposure to several common acute paediatric presentations, such as bronchiolitis (41%), croup (32%) or pneumonia (14%), and to clinical emergencies, including cardiac/respiratory arrests or trauma calls (27%). Across all conditions, average self-reported confidence in assessment and management to the level expected of an FY1 is greater amongst those who observed at least one case (e.g. 7.6/10 compared with 3.6/10 for croup). Students rated exposure through Simulation or VR to be of similar utility to witnessing a clinical scenario on the ward. In free text responses, students unanimously favoured being ‘challenged’ through ‘hands-on’ patient interaction over passive shadowing, where it is ‘easy to zone out.’ In recognition of the fact that such independence is only appropriate in certain clinical situations, many students reported wanting more Simulation and VR teaching. Importantly, students raised the necessity of ‘proper debriefs’ after these sessions to maximise educational value. Discussion and Conclusion: Our questionnaire elicited several student-perceived challenges in paediatric education, including incomplete exposure to common pathologies and limited opportunities for active involvement in patient care. Indeed, these experiences seem to be important predictors of confidence. Quantitative and qualitative feedback suggests that VR and Simulation satisfy students’ self-reported appetite for independent engagement with authentic clinical scenarios. Take-aways: Our findings endorse further development of VR and Simulation as high-yield adjuncts to paediatric education.

Keywords: paediatric emergency education, simulation, virtual reality, medical education

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Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

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Authors: Shivani Singh, Shantanu Nakhare, Kalyani Nair, Rohan Shetty

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As social networking is growing at a rapid pace today it is vital that we work on improving its management. Research has shown that the content present in online social networks may have significant influence on impressionable minds. If such platforms are misused, it will lead to negative consequences. Detecting insults or inappropriate messages continues to be one of the most challenging aspects of Online Social Networks (OSNs) today. We address this problem through a Machine Learning Based Soft Text Classifier approach using Support Vector Machine algorithm. The proposed system acts as a screening mechanism the alerts the user about such messages. The messages are classified according to their subject matter and each comment is labeled for the presence of profanity and insults.

Keywords: machine learning, online social networks, soft text classifier, support vector machine

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Authors: Atakan Aral Ormancı, Tuğçe Arslantaş, Murat Özcü

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This study presents the design and implementation of an experimental chassis-level system for various control applications. Specifically, the height level of the chassis is controlled using proportional integrated derivative, fuzzy logic, and deep learning control methods. Real-time data obtained from height and pressure sensors installed in a 6x2 truck chassis, in combination with pulse-width modulation signal values, are utilized during the tests. A prototype pneumatic system of a 6x2 truck is added to the setup, which enables the Smart Pneumatic Actuators to function as if they were in a real-world setting. To obtain real-time signal data from height sensors, an Arduino Nano is utilized, while a Raspberry Pi processes the data using Matlab/Simulink and provides the correct output signals to control the Smart Pneumatic Actuator in the truck chassis. The objective of this research is to optimize the time it takes for the chassis to level down and up under various loads. To achieve this, proportional integrated derivative control, fuzzy logic control, and deep learning techniques are applied to the system. The results show that the deep learning method is superior in optimizing time for a non-linear system. Fuzzy logic control with a triangular membership function as the rule base achieves better outcomes than proportional integrated derivative control. Traditional proportional integrated derivative control improves the time it takes to level the chassis down and up compared to an uncontrolled system. The findings highlight the superiority of deep learning techniques in optimizing the time for a non-linear system, and the potential of fuzzy logic control. The proposed approach and the experimental results provide a valuable contribution to the field of control, automation, and systems engineering.

Keywords: automotive, chassis level control, control systems, pneumatic system control

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Authors: Kulachai Kultawanich, Prakob Koraneekij, Jaitip Na-Songkhla

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The way of learning has been changed into a new paradigm since the improvement of network and communication technology, so learners have to interact with massive amount of the information. Thus, information literacy has become a critical set of abilities required by every college and university in the world. Connectivism is considered to be an alternative way to design information literacy course in online learning environment, such as Virtual Classroom (VC). With the change of learning pedagogy, VC is employed to improve the social capability by integrating cloud-based technology. This paper aims to study the use of Cloud-based Virtual Classroom (CBVC) in Connectivism learning process to enhance information literacy and self-efficacy of twenty-one undergraduate students who registered in an e-publishing course at Chulalongkorn University. The data were gathered during 6 weeks of the study by using the following instruments: (1) Information literacy test (2) Information literacy rubrics (3) Information Literacy Self-Efficacy (ILSE) Scales and (4) Questionnaire. The result indicated that students have information literacy and self-efficacy posttest mean scores higher than pretest mean scores at .05 level of significant after using CBVC in Connectivism learning process. Additionally, the study identified that the Connectivism learning process proved useful for developing information rich environment and a sense of community, and the CBVC proved useful for developing social connection.

Keywords: cloud-based, virtual classroom, connectivism, information literacy

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Authors: Ben Nwokenkwo, Michael M. Eze, Felix Ike

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The need to study trends in land values around institutions of higher learning cannot be overemphasized. Numerous studies in Nigeria have investigated the economic, and social influence of the sitting of institutions of higher learning at the micro, meso and macro levels. However, very few studies have evaluated the temporal extent at which such institution influences local land values. Since institutions greatly influence both the physical and environmental aspects of their immediate vicinity, attention must be taken to understand the influence of such changes on land values. This study examines the trend in land values using the Mann-Kendall analysis in order to determine if, between its beginning and end, a monotonic increase, decrease or stability exist in the land values across six institutions of higher learning for the period between 2004 and 2014. Specifically, The analysis was applied to the time series of the price(or value) of the land .The results of this study revealed that land values has either been increasing or remained stabled across all the institution sampled. The study finally recommends measures that can be put in place as counter magnets for land values estimation across institutions of higher learning.

Keywords: influence, land, trend, value

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Authors: Ricardo Pinto Mario Covele, Patricio V. Langa, Patrick Swanzy

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The English language has been recognized as a universal medium of instruction in academia, especially in Higher Education Institutions (HEIs) hence exerting enormous influence within the context of research and publication. By extension, the English Language has been embraced by scholars from non-English speaking countries. The purpose of this review was to synthesize the discussions using four databases. Discussion in the English language in the career development of academics, particularly in non-English speaking universities, is largely less visible. This paper seeks to fill this gap and to improve the visibility of the English language in the career development of academics focusing on non-English language speaking universities by undertaking a systematic literature review. More specifically, the paper addresses the language policy, English language learning model as a second language, sociolinguistic field and career development, methods, as well as its main findings. This review analyzed 75 relevant resources sourced from Western Cape’s Library, Scopus, Google scholar, and web of science databases from November 2020 to July 2021 using the PQRS framework as an analytical lens. The paper’s findings demonstrate that, while higher education continues to be under-challenges of English language usage, literature targeting non-English speaking universities remains less discussed than it is often described. The findings also demonstrate the dominance of English language policy, both for knowledge production and dissemination of literature challenging emerging scholars from non-English speaking HEIs. Hence, the paper argues for the need to reconsider the context of non-English language speakers in the English language in the career development of academics’ research, both as empirical fields and as emerging knowledge producers. More importantly, the study reveals two bodies of literature: (1) the instrumentalist approach to English Language learning and (2) Intercultural approach to the English Language for career opportunities, classified as the appropriate to explain the English language learning process and how is it perceived towards scholars’ academic careers in HEIs.

Keywords: English language, public and private universities, language policy, career development, non-English speaking countries

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Authors: Kaushalendra K. Khadanga, Lee Hee Hyol

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Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.

Keywords: active suspension, bending vibration, railway vehicle, vibration control

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Authors: Lana Burmistrova

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Introduction: The influence of visual impairments on several cognitive processes used in the music learning process is an increasingly important area in special education and cognitive musicology. Many children have several visual impairments due to the refractive errors and irreversible inhibitors. However, based on the compensatory neuroplasticity and functional reorganization, congenitally blind (CB) and early blind (EB) individuals use several areas of the occipital lobe to perceive and process auditory and tactile information. CB individuals have greater memory capacity, memory reliability, and less false memory mechanisms are used while executing several tasks, they have better working memory (WM) and short-term memory (STM). Blind individuals use several strategies while executing tactile and working memory n-back tasks: verbalization strategy (mental recall), tactile strategy (tactile recall) and combined strategies. Methods and design: The aim of the pilot study was to substantiate similar tendencies while executing attention, memory and combined auditory tasks in blind and sighted individuals constructed for this study, and to investigate attention, memory and combined mechanisms used in the music learning process. For this study eight (n=8) blind and eight (n=8) sighted individuals aged 13-20 were chosen. All respondents had more than five years music performance and music learning experience. In the attention task, all respondents had to identify pitch changes in tonal and randomized melodic pairs. The memory task was based on the mismatch negativity (MMN) proportion theory: 80 percent standard (not changed) and 20 percent deviant (changed) stimuli (sequences). Every sequence was named (na-na, ra-ra, za-za) and several items (pencil, spoon, tealight) were assigned for each sequence. Respondents had to recall the sequences, to associate them with the item and to detect possible changes. While executing the combined task, all respondents had to focus attention on the pitch changes and had to detect and describe these during the recall. Results and conclusion: The results support specific features in CB and EB, and similarities between late blind (LB) and sighted individuals. While executing attention and memory tasks, it was possible to observe the tendency in CB and EB by using more precise execution tactics and usage of more advanced periodic memory, while focusing on auditory and tactile stimuli. While executing memory and combined tasks, CB and EB individuals used passive working memory to recall standard sequences, active working memory to recall deviant sequences and combined strategies. Based on the observation results, assessment of blind respondents and recording specifics, following attention and memory correlations were identified: reflective attention and STM, reflective attention and periodic memory, auditory attention and WM, tactile attention and WM, auditory tactile attention and STM. The results and the summary of findings highlight the attention and memory features used in the music learning process in the context of blindness, and the tendency of the several attention and memory types correlated based on the task, strategy and individual features.

Keywords: attention, blindness, memory, music learning, strategy

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Authors: Belkhadir Radouane

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In this study, author tried to explore the beliefs of some Moroccan teachers working in the delegations of Safi and Youcefia about the usefulness of first and second languages in learning the third language. More specifically, author attempted to see the extent to which these teachers believe that a first and second language can serve students in learning a third one. The first language in this context is Arabic, the second is French, and the third is English. The teachers’ beliefs were gathered through a questionnaire that was addressed via Google Forms. Then, the results were analyzed using the same application. It was found that teachers are positive about the usefulness of the first and second language in learning the third one, but most of them rarely use in a conscious way activities that serve this purpose.

Keywords: Bilinguilism, teachers beliefs, English as ESL, Morocco

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Authors: Sadeq Al Yaari, Fayza Al Hammadi, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari, Salah Al Yami

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Background: When we further take Arabic grammatical issues into account in accordance with applied linguistic investigations on Arabic as Second Language (ASL) learners, a fundamental issue arises at this point as to the production of speech in Arabic: Oral grammatical errors committed by ASL learners. Aims: Using manual rating as well as computational analytic methodology to test a corpus of recorded speech by Second Language (ASL) learners of Arabic, this study aims to find the areas of difficulties in learning Arabic grammar. More specifically, it examines how and why ASL learners make grammatical errors in their oral speech. Methods: Tape recordings of four (4) Arabic as Second Language (ASL) learners who ranged in age from 23 to 30 were naturally collected. All participants have completed an intensive Arabic program (two years) and 20 minute-speech was recorded for each participant. Having the collected corpus, the next procedure was to rate them against Arabic standard grammar. The rating includes four processes: Description, analysis and assessment. Conclusions: Outcomes made from the issues addressed in this paper can be summarized in the fact that ASL learners face many grammatical difficulties when studying Arabic word order, tenses and aspects, function words, subject-verb agreement, verb form, active-passive voice, global and local errors, processes-based errors including addition, omission, substitution or a combination of any of them.

Keywords: grammar, error, oral, Arabic, second language, learner, applied linguistics.

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Eirini Busack

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Since the outbreak of the Covid-19 pandemic and the sudden transfer to online teaching, teachers have struggled to reconstruct their teaching and learning materials to adapt them to the new reality of online teaching and learning. Consequently, the pupils’ learning was disrupted during this orientation phase. Due to the above situation, teachers from all fields concluded that it is vital that their pupils should be able to continue their learning even without the teacher being physically present. Various websites and applications have been in use since then in hope that pupils will still enjoy a qualitative education; unfortunately, this was often not the case. To address this issue, it was therefore decided to focus the research on the development of digital learning paths. The fundamentals of these learning paths include the implementation of scenario-based learning (digital storytelling), the integration of media-didactic theory to make it pedagogically appropriate for learners, alongside instructional design knowledge and the drive to promote autonomous learners. This particular research is being conducted within the frame of the research project “Sustainable integration of subject didactic digital teaching-learning concepts” (InDiKo, 2020-2023), which is currently conducted at the University of Education Karlsruhe and investigates how pre-service teachers can acquire the necessary interdisciplinary and subject-specific media-didactic competencies to provide their future learners with digitally enhanced learning opportunities, and how these competencies can be developed continuously and sustainably. As English is one of the subjects involved in this project, the English Department prepared a seminar for the pre-service secondary teachers: “Media-didactic competence development: Developing learning paths & Digital Storytelling for English grammar teaching.” During this seminar, the pre-service teachers plan and design a Moodle-based differentiated lesson sequence on an English grammar topic that is to be tested by secondary school pupils. The focus of the present research is to assess the secondary school pupils’ expectations from an English grammar-focused digital learning path created by pre-service English teachers. The nine digital learning paths that are to be distributed to 25 pupils were produced over the winter and the current summer semester as the artifact of the seminar. Finally, the data to be quantitatively analysed and interpreted derive from the online questionnaires that the secondary school pupils fill in so as to reveal their expectations on what they perceive as a stimulating and thus effective grammar-focused digital learning path.

Keywords: digital storytelling, learning paths, media-didactics, autonomous learning

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Authors: Syed Amer Mahmood, Rao Mansor Ali Khan

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This study deals with the remote sensing analysis of tectonic deformation and its implications to understand the regional uplift conditions in the lower Jhelum and eastern Potwar. Identification and mapping of active structures is an important issue in order to assess seismic hazards and to understand the Quaternary deformation of the region. Digital elevation models (DEMs) provide an opportunity to quantify land surface geometry in terms of elevation and its derivatives. Tectonic movement along the faults is often reflected by characteristic geomorphological features such as elevation, stream offsets, slope breaks and the contributing drainage area. The river profile analysis in this region using SRTM digital elevation model gives information about the tectonic influence on the local drainage network. The steepness and concavity indices have been calculated by power law of scaling relations under steady state conditions. An uplift rate map is prepared after carefully analysing the local drainage network showing uplift rates in mm/year. The active faults in the region control local drainages and the deflection of stream channels is a further evidence of the recent fault activity. The results show variable relative uplift conditions along MBT and Riasi and represent a wonderful example of the recency of uplift, as well as the influence of active tectonics on the evolution of young orogens.

Keywords: quaternary deformation, SRTM DEM, geomorphometric indices, active tectonics and MBT

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Authors: Vaida Jurgile

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Intercultural learning is one of the approaches taken to understand the cultural diversity of the modern world and to accept changes in cultural identity and otherness and the expression of tolerance. During intercultural learning, students develop their abilities to interact and communicate with their group members. These abilities help to understand social and cultural differences, to form one’s identity, and to give meaning to intercultural learning. Intercultural education recognizes that a true understanding of differences and similarities of another culture is necessary in order to lay the foundations for working together with others, which contributes to the promotion of intercultural dialogue, appreciation of diversity, and cultural exchange. Therefore, it is important to examine the concept of intercultural learning, revealed through students’ learning experiences and understanding of how this learning takes place and what significance this phenomenon has in higher education. At a scientific level, intercultural learning should be explored in order to uncover the influence of cultural identity, i.e., intercultural learning should be seen in a local context. This experience would provide an opportunity to learn from various everyday intercultural learning situations. Intercultural learning can be not only a form of learning but also a tool for building understanding between people of different cultures. The research object of the study is the process of intercultural learning. The aim of the dissertation is to develop a grounded theory of the process of learning in an intercultural study environment, revealing students’ learning experiences. The research strategy chosen in this study is a constructivist grounded theory (GT). GT is an inductive method that seeks to form a theory by applying the systematic collection, synthesis, analysis, and conceptualization of data. The targeted data collection was based on the analysis of data provided by previous research participants, which revealed the need for further research participants. During the research, only students with at least half a year of study experience, i.e., who have completed at least one semester of intercultural studies, were purposefully selected for the research. To select students, snowballing sampling was used. 18 interviews were conducted with students representing 3 different fields of sciences (social sciences, humanities, and technology sciences). In the process of intercultural learning, language expresses and embodies cultural reality and a person’s cultural identity. It is through language that individual experiences are expressed, and the world in which Others exist is perceived. The increased emphasis is placed on the fact that language conveys certain “signs’ of communication and perception with cultural value, enabling the students to identify the Self and the Other. Language becomes an important tool in the process of intercultural communication because it is only through language that learners can communicate, exchange information, and understand each other. Thus, in the process of intercultural learning, language either promotes interpersonal relationships with foreign students or leads to mutual rejection.

Keywords: intercultural learning, grounded theory, students, other

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Authors: C. Zimmermann, E. Lackner, M. Ebner

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Massive Open Online Courses (MOOCs) are increasingly popular learning hubs that are boasting considerable participant numbers, innovative technical features, and a multitude of instructional resources. Still, there is a high level of evidence showing that almost all MOOCs suffer from a declining frequency of participant activity and fairly low completion rates. In this paper, we would like to share the lessons learned in implementing several design patterns that have been suggested in order to foster participant activity. Our conclusions are based on experiences with the ‘Dr. Internet’ MOOC, which was created as an xMOOC to raise awareness for a more critical approach to online health information: participants had to diagnose medical case studies. There is a growing body of recommendations (based on Learning Analytics results from earlier xMOOCs) as to how the decline in participant activity can be alleviated. One promising focus in this regard is instructional design patterns, since they have a tremendous influence on the learner’s motivation, which in turn is a crucial trigger of learning processes. Since Medieval Age storytelling, micro-learning units and specific comprehensible, narrative structures were chosen to animate the audience to follow narration. Hence, MOOC participants are not likely to abandon a course or information channel when their curiosity is kept at a continuously high level. Critical aspects that warrant consideration in this regard include shorter course duration, a narrative structure with suspense peaks (according to the ‘storytelling’ approach), and a course schedule that is diversified and stimulating, yet easy to follow. All of these criteria have been observed within the design of the Dr. Internet MOOC: 1) the standard eight week course duration was shortened down to six weeks, 2) all six case studies had a special quiz format and a corresponding resolution video which was made available in the subsequent week, 3) two out of six case studies were split up in serial video sequences to be presented over the span of two weeks, and 4) the videos were generally scheduled in a less predictable sequence. However, the statistical results from the first run of the MOOC do not indicate any strong influences on the retention rate, so we conclude with some suggestions as to why this might be and what aspects need further consideration.

Keywords: case study, Dr. internet, experience, MOOCs, design patterns

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Authors: Nidal H. Abu-Zahra, Aruna P. Wanninayake

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Copper Oxide (CuO) is a p-type semiconductor with a band gap energy of 1.5 eV, this is close to the ideal energy gap of 1.4 eV required for solar cells to allow good solar spectral absorption. The inherent electrical characteristics of CuO nano particles make them attractive candidates for improving the performance of polymer solar cells when incorporated into the active polymer layer. The UV-visible absorption spectra and external quantum efficiency of P3HT/PC70BM solar cells containing different weight percentages of CuO nano particles showed a clear enhancement in the photo absorption of the active layer, this increased the power conversion efficiency of the solar cells by 24% in comparison to the reference cell. The short circuit current of the reference cell was found to be 5.234 mA/cm2 and it seemed to increase to 6.484 mA/cm2 in cells containing 0.6 mg of CuO NPs; in addition the fill factor increased from 61.15% to 68.0%, showing an enhancement of 11.2%. These observations suggest that the optimum concentration of CuO nano particles was 0.6 mg in the active layer. These significant findings can be applied to design high-efficiency polymer solar cells containing inorganic nano particles.

Keywords: copper oxide nanoparticle, UV-visible spectroscopy, polymer solar cells, P3HT/PCBM

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Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

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Authors: Haftom Teshale Gebre

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According to the ministry of education’s school improvement program blueprint document (2007), the timely and basic aim of the program is to improve students’ academic achievement through creating conducive teaching and learning environments and with the active involvement of parents in the teaching and learning process. The general objective of the research is to examine the practices of cluster school supervisors in implementing school improvement programs and the major factors affecting the study area. The study used both primary and secondary sources, and the sample size was 93. Twelve people are chosen from each of the two clusters (Edaga Hamus and Adi-kelebes). And cluster ferewyni are Tekli suwaat, Edaga robue, and Kiros Alemayo. In the analysis stage, several interrelated pieces of information were summarized and arranged to make the analysis easily manageable by using statistics and data (STATA). Study findings revealed that the major four domains impacted by school improvement programs through their mean, standard deviation, and variance were 2.688172, 1.052724, and 1.108228, respectively. And also, the researcher can conclude that the major factors of the school improvement program and mostly cluster supervisors were inadequate attention given to supervision service and no experience in the practice of supervision in the study area.

Keywords: cluster, eastern Tigray, Saesie Tsaeda Emba, SPI

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Authors: Davoud Ansari Kejal, Meysam Sabour

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For long, there has been a belief that a reader can easily comprehend a text if he is strong enough in vocabulary and grammatical knowledge but there was no account for the ability of understanding different subjects based on readers’ understanding of the surrounding world which is called world background knowledge. This paper attempts to investigate the reading comprehension process applying the schema theory as an influential factor in comprehending texts, in order to prove the important role of background knowledge in reading comprehension. Based on the discussion, some teaching methods are suggested for employing world background knowledge for an elaborated teaching of reading comprehension in an active learning environment in EFL classes.

Keywords: background knowledge, reading comprehension, schema theory, ELT classes

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Authors: David S. Rosenstein

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The author believes that modern spoken languages should be equally difficult (or easy) to learn, since all normal children learning their native languages do so at approximately the same rate and with the same competence, progressing from easy to more complex grammar and syntax in the same way. Why then, do some languages seem more difficult than others? Perhaps people are referring to the written language, where it may be true that mastering Chinese requires more time than French, which in turn requires more time than Spanish. But this may be marginal, since Chinese and French children quickly catch up to their Spanish peers in reading comprehension. Rather, the real differences in difficulty derive from two sources: hardened L1 language habits trying to cope with contrasting L2 habits; and unfamiliarity with unique L2 characteristics causing faulty expectations. It would seem that effective L2 teaching and learning must take these two sources of difficulty into consideration. The author feels that the latter (faulty expectations) causes the greatest difficulty, making effective teaching and learning somewhat different for each given foreign language. Examples from Chinese and other languages are presented.

Keywords: learning different languages, language learning difficulties, faulty language expectations

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Authors: Gihan Thilakarathna, Fernando Ishara, Rathnayake Yasith, Bandara A. M. R. Y.

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E-learning is a crucial component of intelligent education. Even in the midst of a pandemic, E-learning is becoming increasingly important in the educational system. Several e-learning programs are accessible for students. Here, we decided to create an e-learning framework for children. We've found a few issues that teachers are having with their online classes. When there are numerous students in an online classroom, how does a teacher recognize a student's focus on academics and below-the-surface behaviors? Some kids are not paying attention in class, and others are napping. The teacher is unable to keep track of each and every student. Key challenge in e-learning is online exams. Because students can cheat easily during online exams. Hence there is need of exam proctoring is occurred. In here we propose an automated online exam cheating detection method using a web camera. The purpose of this project is to present an E-learning platform for math education and include games for kids as an alternative teaching method for math students. The game will be accessible via a web browser. The imagery in the game is drawn in a cartoonish style. This will help students learn math through games. Everything in this day and age is moving towards automation. However, automatic answer evaluation is only available for MCQ-based questions. As a result, the checker has a difficult time evaluating the theory solution. The current system requires more manpower and takes a long time to evaluate responses. It's also possible to mark two identical responses differently and receive two different grades. As a result, this application employs machine learning techniques to provide an automatic evaluation of subjective responses based on the keyword provided to the computer as student input, resulting in a fair distribution of marks. In addition, it will save time and manpower. We used deep learning, machine learning, image processing and natural language technologies to develop these research components.

Keywords: math, education games, e-learning platform, artificial intelligence

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Authors: Jocelyn L. Alimondo, Juna O. Sabelo

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This study explored the MTB-MLE implementation practices of teachers in one monolingual elementary school and one multilingual elementary school in Benguet, Philippines. It used phenomenological approach employing participant-observation, focus group discussion and individual interview. Data were gathered using a video camera, an audio recorder, and an FGD guide and were treated through triangulation and coding. From the data collected, varied ways in implementing the MTB-MLE program were noted. These are: Teaching using a hybrid first language, teaching using a foreign LOI, using translation and multilingual instruction, and using L2/L3 to unlock L1. However, these practices come with challenges such as the a conflict between the mandated LOI and what pupils need, lack of proficiency of teachers in the mandated LOI, facing unreceptive parents, stagnation of knowledge resulting from over-familiarity of input, and zero learning resulting from an incomprehensible language input. From the practices and challenges experienced by the teachers, a model of MTB-MLE approach, the 3L-in-one approach, to teaching was created to illustrate the practice which teachers claimed to be the best way to address the challenges besetting them while at the same time satisfying the academic needs of their pupils. From the findings, this paper concludes that despite the challenges besetting the teachers, they still displayed creativity in coming up with relevant teaching practices, the unreceptiveness of some teachers and parents sprung from the fact that they do not understand the real concept of MTB-MLE, greater challenges are being faced by teachers in multilingual school due to the diverse linguistic background of their clients, and the most effective approach in implementing MTB-MLE is the multilingual approach, allowing the use of the pupils’ mother tongue, L2 (Filipino), L3 (English), and other languages familiar to the students.

Keywords: MTB-MLE Philippines, MTB-MLE model, first language, multilingual instruction

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