Search results for: personalized learning

Authors: Sabahat Nadeem, Farman Ali Khan

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Emotions are considered as a vital factor affecting the process of information handling, level of attention, memory capacity and decision making. Latest e-Learning systems are therefore taking into consideration the effective state of learners to make the learning process more effective and enjoyable. One such use of user’s affective information is in the systems that tend to regulate users’ emotions to a state optimally desirable for learning. So for, this objective has been tried to be achieved with the help of teaching strategies, background music, guided imagery, video clips and odors. Nevertheless, we know that colors can affect human emotions. Relationship between color and emotions has a strong influence on how we perceive our environment. Similarly, the colors of the interface can also affect the user positively as well as negatively. This affective behavior of color and its use as emotion regulation agent is not yet exploited. Therefore, this research proposes a Color-based Emotion Regulation Model (CERM), a new framework that can automatically adapt its colors according to user’s emotional state and her personality type and can help in producing a desirable emotional effect, aiming at providing an unobtrusive emotional support to the users of e-learning environment. The evaluation of CERM is carried out by comparing it with classical non-adaptive, static colored learning management system. Results indicate that colors of the interface, when carefully selected has significant positive impact on learner’s emotions.

Keywords: effective learning, e-learning, emotion regulation, emotional design

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Authors: Yan Ma

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Parents in China now are of great enthusiasm to outsource extracurricular lessons and activities to ensure their children’s English learning. This study draws on one year of ethnographic observations and interviews with parents and children in 6 families in Shaoxing, a small city in East China, to explore how parents in different social classes differ in their ideology and investment practice towards their children’s English education. Through comparative analysis, the study reveals though all the families acknowledge the importance of English and there are great similarities among families in the same social class, differences are distinct among those in different social classes with regard to how they perceived the importance and what measures they take. The results also reflect China’s sociocultural and socioeconomic factors that underlined the heated wave of English learning as well as the social, cultural and economic conditions of different families that exert a decisive influence on their children’s learning experience.

Keywords: family background, extracurricular English learning, language ideologies, language management

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Authors: Deependra Prasad Sarraf, Gajendra Prasad Rauniar, Robin Maskey, Rajiv Maharjan, Ashish Shrestha, Ramayan Prasad Kushwaha

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Objectives: To assess the perception of faculties towards online teaching-learning activities conducted during the COVID-19 pandemic and to identify barriers and facilitators to conducting online teaching-learning activities in our context. Methods: A cross-sectional study was conducted among faculties at B. P. Koirala Institute of Health Sciences using a 26-item semi-structured questionnaire. A Google Form was prepared, and its link was sent to the faculties via email. Descriptive statistics were calculated, and findings were presented as tables and graphs. Results: Out of 158 faculties, the majority were male (66.46%), medical faculties (85.44%), and assistant professors (46.84%). Only 16 (10.13%) faculties had received formal training regarding preparing and/or delivering online teaching learning activities. Out of 158, 133 (84.18%) faculties faced technical and internet issues. The most common advantage and disadvantage of online teaching learning activities perceived by the faculties were ‘not limited to time or place’ (94.30%) and ‘lack of interaction with the students’ (82.28%), respectively. Majority (94.3%) of them had a positive perception towards online teaching-learning activities conducted during COVID-19 pandemic. Slow internet connection (91.77%) and frequent electricity interruption (82.91%) were the most common perceived barriers to online teaching-learning. Conclusions: Most of the faculties had a positive perception towards online teaching-learning activities. Academic leaders and stakeholders should provide uninterrupted internet and electricity connectivity, training on online teaching-learning platform, and timely technical support.

Keywords: COVID-19 pandemic, faculties, medical education, perception

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Authors: Khumbuzile M. Ngcobo, Seraphin D. Eyono Obono

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Science and technology has a major impact on many societal domains such as communication, medicine, food, transportation, etc. However, this dominance of modern technology can have a negative unintended impact on indigenous systems, and in particular on indigenous foods. This problem serves as a motivation to this study whose aim is to examine the perceptions of learners on the usefulness of Information and Communication Technologies (ICT's) for learning about indigenous foods. This aim will be subdivided into two types of research objectives. The design and identification of theories and models will be achieved using literature content analysis. The objective on the empirical testing of such theories and models will be achieved through the survey of Hospitality studies learners from different schools in the iLembe and Umgungundlovu Districts of the South African Kwazulu-Natal province. SPSS is used to quantitatively analyse the data collected by the questionnaire of this survey using descriptive statistics and Pearson correlations after the assessment of the validity and the reliability of the data. The main hypothesis behind this study is that there is a connection between the demographics of learners, their perceptions on the usefulness of ICTs for learning about indigenous foods and the following personality an e-learning related theories constructs: computer self-efficacy, trust in ICT systems, and conscientiousness; as suggested by existing studies on learning theories. This hypothesis was fully confirmed by the survey conducted by this study except for the demographic factors where gender and age were not found to be determinant factors of learners’ perceptions on the usefulness of ICT's for learning about indigenous foods.

Keywords: e-learning, indigenous foods, information and communication technologies, learning theories, personality

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Authors: Polina Pekker

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This work analyzes the role of lecturers in e-learning in Russia. It is based on qualitative research of lecturers who conduct courses on Russian national platforms of open education. The platform is based on edx software (provider of massive open online courses). The interviews with e-learning lecturers were conducted: from December 2015 till January 2016 and from April 2016 till May 2016. The results of interviews (face-to-face, telephone, skype) show, firstly, the difference between the role of lecturers in e-learning and in traditional education and, secondly, that the competition between lecturers is high in Russia. The results of interviews in Russia show that e-learning lecturer should have several special professional competences: the ability to keep attention of audiences without real contact, the ability to work on camera and competences related with e-learning course support (test, forum, communication on forum and etc.) It is concluded that lecturers need special course on acting and speech skills and on conducting and organizing of e-learning course in Russia. It is planned to conduct French study. When results from French research will be totally ready, they will be compared to Russian. As well French platform, France Universite Numerique, was launched earlier, in January 2014, so Russian lecturers should get best practice from the French colleagues.

Keywords: e-courses lecturer, e-learning, professional competences of lecturers, national Russian and French platforms of open education

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Authors: Paul Lam, Chi Him Chan, Alan Tse

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Language laboratories have been widely used in language learning, starting in the middle of the last century as one of the earliest forms of educational technology. They are designed to assist students’ language learning with technological innovations. Traditional language laboratories provide individual workstations that allow students to access multimedia language resources. In this type of facility, students can train their listening and speaking abilities, and teachers can also assess the performance of an individual student. Although such a setting promotes a student-centered pedagogy by encouraging students to work at their own pace and according to their own needs, it still favours a traditional, behaviourist language learning pedagogy which focuses on repetitive drilling. The change of pedagogies poses challenges to both the teachers and the facilities. The peer-learning pedagogy advocates that language learning should focus on the social aspect, which emphasizes the importance of everyday communication in language learning. The self-access, individual workstation language laboratories may not be able to provide the flexibility for interaction in the new pedagogies. Modern advancement in technology is another factor that drove our language laboratory renovation. In particular, mobile and wireless technology enabled the use of smaller and more flexible devices, making possible much clever use of space. The Chinese University of Hong Kong (CUHK) renovated nine existing language laboratories to provide lighter and more advanced equipment, movable tables, and round desks. These facilities allow more flexibility and encourage students’ interaction. It is believed that the renovated language laboratories can serve different peer learning activities and thus support peer-learning pedagogies in language teaching and learning. A survey has been conducted to collect comments from the teachers who have used the renovated language laboratories and received forty-four response. The teachers’ comments reveal that they experienced different challenges in using the renovated language laboratories, and there is a need to provide guidance to teachers during the technological and pedagogical transition. For example, teachers need instruction on using the newly installed devices such as touch-monitor and visualizer. They also need advice on planning new teaching and learning activities. Nevertheless, teachers appreciated that the renovated language laboratories are flexible and provide more spaces for different learning activities.

Keywords: language laboratories, language learning, peer-learning, student interaction

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Authors: Yolina A. Petrova, Georgi I. Petkov

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The paper presents a symbolic model for category learning and categorization (called RoleMap). Unlike the other models which implement learning in a separate working mode, role-governed category learning and categorization emerge in RoleMap while it does its usual reasoning. The model is based on several basic mechanisms known as reflecting the sub-processes of analogy-making. It steps on the assumption that in their everyday life people constantly compare what they experience and what they know. Various commonalities between the incoming information (current experience) and the stored one (long-term memory) emerge from those comparisons. Some of those commonalities are considered to be highly important, and they are transformed into concepts for further use. This process denotes the category learning. When there is missing knowledge in the incoming information (i.e. the perceived object is still not recognized), the model makes anticipations about what is missing, based on the similar episodes from its long-term memory. Various such anticipations may emerge for different reasons. However, with time only one of them wins and is transformed into a category member. This process denotes the act of categorization.

Keywords: analogy-making, categorization, category learning, cognitive modeling, role-governed categories

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Authors: Shenlun Chen, Leonard Wee

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Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

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Authors: Susan Diamond

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Machine Learning workloads have traditionally been run in high-performance computing (HPC) environments, where users log in to dedicated machines and utilize the attached GPUs to run training jobs on huge datasets. Training of large neural network models is very resource intensive, and even after exploiting parallelism and accelerators such as GPUs, a single training job can still take days. Consequently, the cost of hardware is a barrier to entry. Even when upfront cost is not a concern, the lead time to set up such an HPC environment takes months from acquiring hardware to set up the hardware with the right set of firmware, software installed and configured. Furthermore, scalability is hard to achieve in a rigid traditional lab environment. Therefore, it is slow to react to the dynamic change in the artificial intelligent industry. Watson Deep Learning as a service, a cloud-based deep learning platform that mitigates the long lead time and high upfront investment in hardware. It enables robust and scalable sharing of resources among the teams in an organization. It is designed for on-demand cloud environments. Providing a similar user experience in a multi-tenant cloud environment comes with its own unique challenges regarding fault tolerance, performance, and security. Watson Deep Learning as a service tackles these challenges and present a deep learning stack for the cloud environments in a secure, scalable and fault-tolerant manner. It supports a wide range of deep-learning frameworks such as Tensorflow, PyTorch, Caffe, Torch, Theano, and MXNet etc. These frameworks reduce the effort and skillset required to design, train, and use deep learning models. Deep Learning as a service is used at IBM by AI researchers in areas including machine translation, computer vision, and healthcare. 

Keywords: deep learning, machine learning, cognitive computing, model training

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Authors: Xun Li, Haojie Wang

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Federated learning is a kind of distributed training and centralized training mode, which is of great value in the protection of user privacy. In order to solve the problem that the model is vulnerable to backdoor attacks in federated learning, a backdoor attack detection method based on a weighted k-medoids algorithm is proposed. First of all, this paper collates the update parameters of the client to construct a vector group, then uses the principal components analysis (PCA) algorithm to extract the corresponding feature information from the vector group, and finally uses the improved k-medoids clustering algorithm to identify the normal and backdoor update parameters. In this paper, the backdoor is implanted in the federation learning model through the model replacement attack method in the simulation experiment, and the update parameters from the attacker are effectively detected and removed by the defense method proposed in this paper.

Keywords: federated learning, backdoor attack, PCA, k-medoids, backdoor defense

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Authors: Anum Ali, Kashaf ad Dooja, Asif Saleem

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The future smart cities trend will be towards Internet of Things (IoT); IoT creates dynamic connections in a ubiquitous manner. Smart cities offer ease and flexibility for daily life matters. By using small devices that are connected to cloud servers based on IoT, network traffic between these devices is growing exponentially, whose security is a concerned issue, since ratio of cyber attack may make the network traffic vulnerable. This paper discusses the latest machine learning approaches in related work further to tackle the increasing rate of cyber attacks, machine learning algorithm is applied to IoT-based network traffic data. The proposed algorithm train itself on data and identify different sections of devices interaction by using supervised learning which is considered as a classifier related to a specific IoT device class. The simulation results clearly identify the attacks and produce fewer false detections.

Keywords: IoT, traffic security, deep learning, classification

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Authors: Rana Alaa El-Deen Ahmed, M. Elemam Shehab, Shereen Morsy, Nermeen Mekawie

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With the growing popularity and acceptance of e-commerce platforms, users face an ever increasing burden in actually choosing the right product from the large number of online offers. Thus, techniques for personalization and shopping guides are needed by users. For a pleasant and successful shopping experience, users need to know easily which products to buy with high confidence. Since selling a wide variety of products has become easier due to the popularity of online stores, online retailers are able to sell more products than a physical store. The disadvantage is that the customers might not find products they need. In this research the customer will be able to find the products he is searching for, because recommender systems are used in some ecommerce web sites. Recommender system learns from the information about customers and products and provides appropriate personalized recommendations to customers to find the needed product. In this paper eleven classification algorithms are comparatively tested to find the best classifier fit for consumer online shopping attitudes and behavior in the experimented dataset. The WEKA knowledge analysis tool, which is an open source data mining workbench software used in comparing conventional classifiers to get the best classifier was used in this research. In this research by using the data mining tool (WEKA) with the experimented classifiers the results show that decision table and filtered classifier gives the highest accuracy and the lowest accuracy classification via clustering and simple cart.

Keywords: classification, data mining, machine learning, online shopping, WEKA

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Authors: Anastassis Kozanitis, Diane Leduc, Alain Stockless

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This paper presents preliminary results from a two-year funded research program looking to analyze and understand the relationship between high cognitive engagement, higher order cognitive processes employed in situations of complex learning tasks, and the use of active learning pedagogies in engineering undergraduate programs. A mixed method approach was used to gauge student engagement and their cognitive processes when accomplishing complex tasks. Quantitative data collected from the self-report cognitive engagement scale shows that deep learning approach is positively correlated with high levels of complex learning tasks and the level of student engagement, in the context of classroom active learning pedagogies. Qualitative analyses of in depth face-to-face interviews reveal insights into the mechanisms influencing students’ cognitive processes when confronted with open-ended problem resolution. Findings also support evidence that students will adjust their level of cognitive engagement according to the specific didactic environment.

Keywords: cognitive engagement, deep and shallow strategies, engineering programs, higher order cognitive processes

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Authors: Luis H. Gonzalez-Guerra, Armandina J. Leal-Flores

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Students attending classrooms nowadays are habituated to use digital devices all the time and for multiple things. They have been familiar with digital technology throughout their lives so they have developed skills that should be naturally adopted as part of their study strategies. New learning styles require taking in consideration the use of models that support and promote student motivation for learning and development of their creative thinking skills. To achieve student learning in programming courses, different strategies are used. One of them is a collaboration between students, which is a tool which faculty can take advantage of when teaching these kinds of courses. Moreover, cooperation is an essential skill that society should reinforce in order to promote a healthy social environment and cohabitation. Nevertheless, students will still require support and advice to get a complete and correct programming solution to successfully address and solve the problems given throughout the course. This paper present a model where collaboration between students is associated with an automatic tutoring platform providing an excellent approach for the individual learning in collaborative activities in programming courses, and also motivates students to increase their knowledge regarding the topics covered in the classroom.

Keywords: automatic tutoring, collaboration learning, creative thinking, motivation

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Authors: Daniel Ecler

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The aim of this paper was to find out how Chinese university students perceive distance learning compared to full-time teaching, to reveal its advantages and disadvantages, and to try to find what elements could be implemented in regular full-time teaching in order to make it more effective. Recent events have shown that online teaching has a significant role to play in the field of education and needs to be given increased attention and scrutiny. For this purpose, a research survey was conducted using semi-structured questionnaires, which aimed to determine the attitudes of Chinese university students to the phenomenon of distance learning. The results of this survey revealed that most students prefer distance learning to full-time teaching, mainly because it gives them more freedom to participate in teaching, regardless of the environment in which they are currently located. In conclusion, it is necessary to mention that the possibility to participate virtually in teaching from anywhere is a huge advantage that could become part of regular teaching in the future. However, further research into this issue will be necessary.

Keywords: distance learning, full-time teaching, Chinese college students, cultural background

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Authors: Matthias Grunke

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In this qualitative study, we interviewed a young man with learning disabilities who played professional baseball for two years. Individuals with severe academic challenges constitute one of the most vulnerable groups of our society. Science has to find ways on how to arm them against life’s challenges and help them to cope with the many risk factors that they are usually confronted with. Team sports like baseball seem to be a suitable means for that purpose. In the interview, our participant talked about his life as a student with severe learning difficulties and related how his career in baseball made his academic challenges appear much less significant. He gave some meaningful insights into what helped him to build a happy and fulfilling life for himself, not only in spite of his challenges but also because of what he's learning disabilities taught him. Support from significant others, a sense of purpose, his fighting spirit ignited by sports, and the success that he experienced on the baseball field were among the most relevant factors. Overall, this study highlights the importance of finding an outlet for young people with learning disabilities where their academic difficulties retreat into the background and their talents are validated.

Keywords: baseball, inclusion, learning disabilities, resilience

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Authors: Shoba Bandi-Rao

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The lack of college readiness is one of the major contributors to low graduation rates at community colleges, especially among educationally and financially disadvantaged students. About 45% of underprepared high school graduates are required to complete ‘remedial’ reading/writing courses before they can begin taking college-level courses. Mobile apps present ‘bite-size’ learning materials that can be useful for practicing certain literacy skills, such as vocabulary learning. The convenience of mobile phones is ideal for a majority of students at community colleges who hold full or part-time jobs. Mobile apps allow students to learn during small ‘chunks’ of time available to them outside of the class—during subway commute, between classes, etc. Learning with mobile apps is a relatively new area in research, and their effectiveness for learning new words has been inconclusive. Using Mishra & Koehler’s TPCK theoretical framework, this study explored the effectiveness of the mobile app (Quizlet) for learning one hundred common college-level words in ‘remedial’ writing class over one semester. Each week, before coming to class, students studied a list of 10-15 words presented in context within sentences. Students came across these words in the article they read in class making their learning more meaningful. A pre and post-test measured the number of words students knew, learned and remembered. Statistical analysis shows that students performed better by 41% on the post-test indicating that the mobile app was helpful for learning words. Students also completed a short survey each week that sought to determine the amount of time students spent on the vocabulary app. A positive correlation was found between the amount of time spent on the mobile app and the number of words learned. The goal of this research is to capitalize on the convenience of smartphones to (1) better prepare them for college-level course work, and (2) contribute to current literature on mobile learning.

Keywords: mobile learning, vocabulary learning, literacy skills, Quizlet

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Authors: Samiah Alammari, Nassim Ammour

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When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on HSI dataset Indian Pines. The results confirm the capability of the proposed method.

Keywords: continual learning, data reconstruction, remote sensing, hyperspectral image segmentation

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Authors: Adedolapo Taiwo Adeyemi, Success Ayodeji Fasanmi

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The emergence of the coronavirus pandemic and the rate of the spread affected a lot of activities across the world. This led to the introduction of online learning modes in several countries after institutions were shut down. Unfortunately, most public universities in Nigeria could not switch to the online mode because they were not prepared for it, as they do not have the technological capacity to support a full online learning mode. This study examines the readiness of university and the attitude of undergraduates towards online learning mode in Obafemi Awolowo University (OAU), Ile Ife. It investigated the skills and competencies of students for online learning as well as the university’s readiness towards online learning mode; the effort was made to identify challenges of online teaching and learning in the study area, and suggested solutions were advanced. OAU was selected because it is adjudged to be the leading Information and Communication Technology (ICT) driven institution in Nigeria. The descriptive survey research design was used for the study. A total of 256 academic staff and 1503 undergraduates were selected across six faculties out of the thirteen faculties in the University. Two set of questionnaires were used to get responses from the selected respondents. The result showed that students have the skills and competence to operate e-learning facilities but are faced with challenges such as high data cost, erratic power supply, and lack of gadgets, among others. The study found out that the university was not prepared for online learning mode as it lacks basic technological facilities to support it. The study equally showed that while lecturers possess certain skills in using some e-learning applications, they were limited by the unavailability of online support gadgets, poor internet connectivity, and unstable power supply. Furthermore, the assessment of student attitude towards online learning mode shows that the students found the online learning mode very challenging as they had to bear the huge cost of data. Lecturers also faced the same challenge as they had to pay a lot to buy data, and the networks were sometimes unstable. The study recommended that adequate funding needs to be provided to public universities by the government while the management of institutions must build technological capacities to support online learning mode in the hybrid form and on a full basis in case of future emergencies.

Keywords: universities, online learning, undergraduates, attitude

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Authors: Atara Shriki, Ilana Lavy

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Teaching for the first time an online course dealing with the history of mathematics, we were struggling with questions related to the design of a proper learning environment (LE). Thirteen high school mathematics teachers, M.Ed. students, attended the course. The teachers were engaged in independent reading of mathematical texts, a task that is recognized as complex due to the unique characteristics of such texts. In order to support the learning processes and develop skills that are essential for succeeding in learning online (e.g. self-regulated learning skills, meta-cognitive skills, reflective ability, and self-assessment skills), the LE comprised of three components aimed at “scaffolding” the learning: (1) An online "self-feedback" questionnaires that included drill-and-practice questions. Subsequent to responding the questions the online system provided a grade and the teachers were entitled to correct their answers; (2) Open-ended questions aimed at stimulating critical thinking about the mathematical contents; (3) Reflective questionnaires designed to assist the teachers in steering their learning. Using a mixed-method methodology, an inquiry study examined the learning processes, the learners' difficulties in reading the mathematical texts and on the unique contribution of each component of the LE to the ability of teachers to comprehend the mathematical contents, and support the development of their learning skills. The results indicate that the teachers found the online feedback as most helpful in developing self-regulated learning skills and ability to reflect on deficiencies in knowledge. Lacking previous experience in expressing opinion on mathematical ideas, the teachers had troubles in responding open-ended questions; however, they perceived this assignment as nurturing cognitive and meta-cognitive skills. The teachers also attested that the reflective questionnaires were useful for steering the learning. Although in general the teachers found the LE as supportive, most of them indicated the need to strengthen instructor-learners and learners-learners interactions. They suggested to generate an online forum to enable them receive direct feedback from the instructor, share ideas with other learners, and consult with them about solutions. Apparently, within online LE, supporting learning merely with respect to cognitive aspects is not sufficient. Leaners also need an emotional support and sense a social presence.

Keywords: cognitive and meta-cognitive skills, independent reading of mathematical texts, online learning environment, self-regulated learning skills

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Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

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Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

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Authors: Nirit Raichel, Dorit Alt

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Although university teaching is claimed to have a special task to support students in adopting ways of thinking and producing new knowledge anchored in scientific inquiry practices, it is argued that students' habits of learning are still overwhelmingly skewed toward passive acquisition of knowledge from authority sources rather than from collaborative inquiry activities. In order to overcome this critical inadequacy between current educational goals and instructional methods, the LLAF consortium is aimed at developing updated instructional practices that put a premium on adaptability to the emerging requirements of present society. LLAF has created a practical guide for teachers containing updated pedagogical strategies based on the constructivist approach for learning, arranged along Delors’ four theoretical ‘pillars’ of education: Learning to know, learning to do, learning to live together, and learning to be. This presentation will be limited to problem-based learning (PBL), as a strategy introduced in the second pillar. PBL leads not only to the acquisition of technical skills, but also allows the development of skills like problem analysis and solving, critical thinking, cooperation and teamwork, decision- making and self-regulation that can be transferred to other contexts. This educational strategy will be exemplified by a case study conducted in the pre-piloting stage of the project. The case describes a three-fold process implemented in a postgraduate course for in-service teachers, including: (1) learning about PBL (2) implementing PBL in the participants' classes, and (3) qualitatively assessing the contributions of PBL to students' outcomes. An example will be given regarding the ways by which PBL was applied and assessed in civic education for high-school students. Two 9th-grade classes have participated the study; both included several students with learning disability. PBL was applied only in one class whereas traditional instruction was used in the other. Results showed a robust contribution of PBL to students' affective and cognitive outcomes as reflected in their motivation to engage in learning activities, and to further explore the subject. However, students with learning disability were less favorable with this "active" and "annoying" environment. Implications of these findings for the LLAF project will be discussed.

Keywords: problem-based learning, higher education, pedagogical strategies

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Authors: Ram A. Giri, Amna Bedri, Abdou Niane

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Exclusion in education on the basis of language in multilingual contexts operates at multiple levels. Learners of diverse ethnolinguistic backgrounds are often expected to learn through English and are pushed further down the learning ladder if they also have to access education through Information and Communication Technology (ICT). The paper explores marginalized children’s lived experiences in accessing technology and English in four low-income countries in Africa and Asia. Based on the findings of the first phase of a multinational qualitative research study, we report on the factors or barriers that affect children’s access, opportunities and motivation for learning through technology and English. ICT and English - the language of ICT and education - can enhance learning and can even be essential. However, these two important keys to education can also function as barriers to accessing quality education, and therefore as zones of exclusion. This paper looks into how marginalized children (aged 13-15) engage in learning through ICT and English and to what extent the restrictive access and opportunities contribute to the widening of the already existing gap in education. By applying the conceptual frameworks of “access and accessibility of learning” and “zones of exclusion,” the paper elucidates how the barriers prevent children’s effective engagement with learning and addresses such questions as to how marginalized children access technology and English for learning; whether the children value English, and what their motivation and opportunity to learn it are. In addition, the paper will point out policy and pedagogic implications.

Keywords: exclusion, inclusion, inclusive education, marginalization

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Authors: Yuqing Sun

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Chinese has been regarded as one of the most difficult languages in learning due to its complex spelling structure, difficult pronunciation, as well as its varying forms. Since vocabulary acquisition is the basic process to acquire a language, to express yourself, to compose a sentence, and to conduct a communication, so learning the vocabulary is of great importance. However, the vocabulary contains pronunciation, spelling, recognition and application which may seem as a huge work. This may pose a question for the language teachers (language teachers in China who teach Chinese to the foreign students): How to teach them in an effective way? Traditionally, teachers have no choice but teach it all by themselves, then with the development of technology, they can use computer as a tool to help them (Computer Assisted Language Learning or CALL). Now, they move into the Mobile Assisted Language Learning (MALL) method to guide their teaching, upon which the appraisal is convincing. It diversifies the learning material and the way of output, which can activate learners’ curiosity and accelerate their understanding. This paper will focus on actual case studies occurring in the universities in China of teaching the foreign students to learn Chinese, and the analysis of the utilization of WeChat channel as an example of MALL model to explore the active role of MALL to enhance the effectiveness of Chinese vocabulary acquisition.

Keywords: Chinese, vocabulary acquisition, MALL, case

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Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

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The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

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Authors: Kenneth N. Ohei, Roelien Brink

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For decades, teaching and learning processes have centered on the traditional approach (Web 1.0) that promoted teacher-directed pedagogical practices. Currently, there is a realization that the traditional approach is not adequate to effectively address and improve all student-learning outcomes. The subsequent incorporation of social software, Information, and Communication Technology (ICT) tools in universities may serve as complementary to support educational goals, offering students the affordability and opportunity to educational choices and learning platforms. Consequently, educators’ inability to incorporate these instructional ICT tools in their teaching and learning practices remains a challenge. This will signify that educators still lack the ICT skills required to administer lectures and bridging learning gaps. This study probes a methodological concept with the aim of developing a framework towards the adoption of social software in HES to help facilitate business processes and can build social presence among students. A mixed method will be appropriate to develop a comprehensive framework needed in Higher Educational System (HES). After research have been conducted, the adoption of social software will be based on the developed comprehensive framework which is supposed to impact positively on education and approach of delivery, improves learning experience, engagement and finally, increases educational opportunities and easy access to educational contents.

Keywords: blended and integrated learning, learning experience and engagement, higher educational system, HES, information and communication technology, ICT, social presence, Web 1.0, Web 2.0, Web 3.0

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Authors: Nikolina Ribarić

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E-learning is most commonly defined as a set of applications and processes, such as Web-based learning, computer-based learning, virtual classrooms, and digital collaboration, that enable access to instructional content through a variety of electronic media. The main goal of an e-learning system is learning, and the way to evaluate the impact of an e-learning system is by examining whether students learn effectively with the help of that system. Testmoz is a program for online preparation of knowledge evaluation assignments. The program provides teachers with computer support during the design of assignments and evaluating them. Students can review and solve assignments and also check the correctness of their solutions. Research into the increase of motivation by the practice of providing teaching content by applying online tests prepared in the Testmoz program was carried out with students of the 8th grade of Ljubo Babić Primary School in Jastrebarsko. The students took the tests in their free time, from home, for an unlimited number of times. SPSS was used to process the data obtained by the research instruments. The results of the research showed that students preferred to practice teaching content and achieved better educational results in chemistry when they had access to online tests for repetition and practicing in relation to subject content which was checked after repetition and practicing in "the classical way" -i.e., solving assignments in a workbook or writing assignments in worksheets.

Keywords: chemistry class, e-learning, motivation, Testmoz

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Authors: Laura M. Schwarz

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WebQuests are an internet-based interactive teaching/learning tool and utilize a scaffolded methodology. WebQuests employ critical thinking, afford inquiry-based constructivist learning, and readily employ Bloom’s Taxonomy. WebQuests have generally been used as instructional technology tools in primary and secondary education and have more recently grown in popularity in higher education. The study of the efficacy of WebQuests as an instructional approach to learning, however, has been limited, particularly in the nursing education arena. The purpose of this mixed-methods study was to determine nursing students’ perceptions of the effectiveness of the Nursing WebQuest as a teaching/learning strategy for holistic nursing-related content. Quantitative findings (N=42) suggested that learners were active participants, used reflection, thought of new ideas, used analysis skills, discovered something new, and assessed the worth of something while taking part in the WebQuests. Qualitative findings indicated that participants found WebQuest positives as easy to understand and navigate; clear and organized; interactive; good alternative learning format, and used a variety of quality resources. Participants saw drawbacks as requiring additional time and work; and occasional failed link or link causing them to lose their location in the WebQuest. Recommendations include using larger sample size and more diverse populations from various programs and universities. In conclusion, WebQuests were found to be an effective teaching/learning tool as positively assessed by study participants.

Keywords: holistic nursing, nursing education, teaching/learning strategy, WebQuests

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Authors: Fabio Fabris, Alex A. Freitas

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Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: algorithm recommendation, meta-learning, bioinformatics, hierarchical classification

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Authors: Yashi Ye

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Principles play vital roles in shaping the school culture and promoting teachers' professional learning by exerting their leadership. In the changing time of the 21st century, the creative leadership of school leaders is increasingly important in cultivating the professional learning communities of teachers for eventually improving student performance in every continent. This study examines under what conditions and how principal creative leadership contributes to teachers’ professional learning and school culture. Data collected from 632 teachers in 30 primary and middle schools in the cities of Chengdu and Chongqing in mainland China are analyzed using structural equation modeling and bootstrapping tests. A moderated mediation model of principle creative leadership effects is used to analyze professional teacher learning and school culture in which the mediator will be school culture and the moderator will be power distance orientation. The results indicate that principal creative leadership has significant direct and indirect effects on teachers' professional learning. A positive correlation between principal creative leadership, professional teacher learning, and school culture is observed. Further model testing found that teacher power distance orientation moderated the significant effect of principal creative leadership on school culture. When teachers perceived higher power distance in teacher-principal relations, the effects of principal creative leadership were stronger than for those who perceived low power distance. The results indicate the “culture change” in the young generation of teachers in China, and further implications to understanding the cultural context in the field of educational leadership are discussed.

Keywords: power distance orientation, principal creative leadership, school culture, teacher professional learning

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