Search results for: activity learning

Authors: Ying Su, Morgan C. Wang

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Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

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Authors: Ayşegül Çabuk, Mine Işıksal

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Mathematics is a sense-making activity so that it requires meaningful learning. Hence based on this idea, meaningful mathematical connections are necessary to learn mathematics. At that point, the major question has become that which educational methods can provide opportunities to provide mathematical connections and to understand mathematics. The amalgam of reasoning and proof can be the one of the methods that creates opportunities to learn mathematics in a meaningful way. However, even if reasoning and proof should be included from prekindergarten to grade 12, studies in literature generally include secondary school students and pre-service mathematics teachers. With the light of the idea that the amalgam of reasoning and proof has significant effect on middle school students' mathematical learning, this study aims to investigate middle grade students' tendencies while reasoning the correctness of statements related to numbers. The sample included 272 middle grade students, specifically 69 of them were sixth grade students (25.4%), 101 of them were seventh grade students (37.1%) and 102 of them were eighth grade students (37.5%). Data was gathered through an achievement test including 2 essay types of problems about algebra. The answers of two items were analyzed both quantitatively and qualitatively in terms of students' solutions strategies while reasoning the correctness of the statements. Similar on the findings in the literature, most of the students, in all grade levels, used numerical examples to judge the statements. Moreover the results also showed that the majority of these students appear to believe that providing one or more selected examples is sufficient to show the correctness of the statement. Hence based on the findings of the study, even students in earlier ages have proving and reasoning abilities their reasoning's generally based on the empirical evidences. Therefore, it is suggested that examples and example-based reasoning can be a fundamental role on to generate systematical reasoning and proof insight in earlier ages.

Keywords: reasoning, mathematics learning, middle grade students

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Authors: Jindriska Svobodova, Jan Novotny

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A teacher’s attitude to creativity plays an essential role in the thinking development of his/her students. The purpose of this study is to understand if a science teacher's personal creativity can modify his/her ability to produce various kinds of questions. This research used an education activity based on cosmic sketches and pictures by K.E. Tsiolkovsky, the founder of astronautics, to explore if any relationship between individual creativity and the asking questions skill exists. As a screening instrument, which allows an assessment of the respondent's creative potential, a common test of creative thinking was used. The results of the creativity test and the diversity of the questions are mentioned.

Keywords: science education, active learning, physics teaching, religious cosmology

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Authors: Fuad M. Alkoot

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The main component of a machine learning system is the classifier. Classifiers are mathematical models that can perform classification tasks for a specific application area. Additionally, many classifiers are combined using any of the available methods to reduce the classifier error rate. The benefits gained from the combination of multiple classifier designs has motivated the development of diverse approaches to multiple classifiers. We aim to investigate using fractal geometry to develop an improved classifier combiner. Initially we experiment with measuring the fractal dimension of data and use the results in the development of a combiner strategy.

Keywords: fractal geometry, machine learning, classifier, fractal dimension

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Authors: Emanuel Koseos

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Data-Driven Decision Making (DDDM) refers to making decisions that are based on historical data in order to inform practice, develop strategies and implement policies that benefit organizational settings. In educational technology, DDDM facilitates the implementation of differential educational learning approaches such as Educational Data Mining (EDM) and Competency-Based Education (CBE), which commonly target university classrooms. There is a current need for DDDM models applied to middle and secondary schools from a concern for assessing the needs, progress and performance of students and educators with respect to regional standards, policies and evolution of curriculums. To address these concerns, we propose a DDDM reference model developed using educational key process initiatives as inputs to a machine learning framework implemented with statistical software (SAS, R) to provide a best-practices, complex-free and automated approach for educators at their regional level. We assessed the efficiency of the model over a six-year period using data from 45 schools and grades K-12 in the Langley, BC, Canada regional school district. We concluded that the model has wider appeal, such as business learning systems.

Keywords: competency-based learning, data-driven decision making, machine learning, secondary schools

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Authors: Mourad Ben Bennani

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Views of language and language learning have undergone a tremendous change over the last decades. Language is no longer seen as a set of structured rules. It is rather viewed as a tool of interaction and communication. This shift in views has resulted in change in viewing language learning, which gave birth to various approaches and methodologies of language teaching. Two of these approaches are content-based instruction and content and language integrated learning (CLIL). These are similar approaches which integrate content and foreign/second language learning through various methodologies and models as a result of different implementations around the world. This presentation deals with sociocultural view of CBI and CLIL. It also defines language and content as vital components of CBI and CLIL. Next it reviews the origins of CBI and the continuum perspectives and CLIL definitions and models featured in the literature. Finally it summarizes current aspects around research in program evaluation with a focus on the benefits and challenges of these innovative approaches for second language teaching.

Keywords: CBI, CLIL, CBI continuum, CLIL models

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Authors: Thuy Phan, Stephanie Luallin

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Inclusive education policies have demonstrated benefits for students with and without disabilities in the US. There are several laws that relate to inclusive education, such as 'No Child Left Behind', 'The Individuals with Disabilities Education Act'. However, the application of these inclusive education laws and policies vary per state and school district. Classroom teachers in an inclusive classroom often experience confusion as to how to apply these policies in order to create appropriate inclusive learning environments that meet the abilities and needs of their diverse student population. The study aims to investigate teachers’ perspective of their capacities to create an appropriate learning environment for their diverse student population including students with disabilities. Qualitative method is implemented in this study, using open-end interview questions to investigate teachers’ perspective of their capacities to create an appropriate inclusive learning environment for all students based on current inclusive education laws and district policies in the state of Colorado, USA. These findings may indicate a lack of confidence in teachers’ capacity to create appropriate inclusive learning environments based on laws and district policies; including challenges that classroom teachers may experience in creating inclusive learning environments. The purpose of this study is to examine the adequate preparation of classroom teachers in creating inclusive classrooms with the intent of determining implications for developing policies in inclusive education.

Keywords: educator’s capacity, inclusive education, inclusive learning environment, policy

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Authors: Islam Elsayed Hussein Ali, Stefan M. Wagner

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Smartphone and tablet computers, as well as other ultra portable devices, have already gained enough critical mass to be considered mainstream devices, being present in the daily lives of millions of higher education students. Many universities throughout the world have already adopted or are planning to adopt mobile technologies in many of their courses as a better way to connect students with the subjects they are studying. These new mobile platforms allow students to access content anywhere/anytime to immerse himself/herself into that content (alone or interacting with teachers or colleagues via web communication forms) and to interact with that content in ways that were not previously possible. This paper plans to provide a thorough overview of the possibilities and consequences of m-learning in higher education environments as a gateway to ubiquitous learning – perhaps the ultimate form of learner engagement, since it allows the student to learn, access and interact with important content in any way or at any time or place he might want so the objective of the study is to examine how the usage of mobile phones for m-learning differs between heavy and light mobile phone users at TU Braunschweig. Heavy mobile phone users are hypothesized to have access to/subscribe to one type of mobile content than light mobile phone users, to have less frequent access to, subscribe to or purchase mobile content within the last year than light mobile phone users, and to pay less money for mobile learning, its content and mobile games than light mobile phone users.

Keywords: mobile learning, technologies, applications, higher education

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Authors: Pakakrong Thongdeeying, Srisopa Ruangnoo, Arunporn Itharat

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The rhizomes of Smilax corbularia Kunth have long been used as common ingredients in anticancer preparations. Thus, the objective of this study is to investigate cytotoxicity of S. corbularia and its ingredients against cholangiocarcinoma cell line (KKU-M156) by SRB assay. Ethanolic and water extracts of S. corbularia rhizomes were obtained using the procedures followed by Thai traditional doctors. Bioassay guided isolation was used to isolate cytotoxic compounds. The results revealed that the ethanolic extract of S. corbularia exhibited activity against KKU-M156 cell line with an IC50 value of 84.53±1.62 µg/ml, but the water extract showed no cytotoxic activity. Three flavonoid compounds [astilbin (1), engeletin (2), and quercetin (3)] were isolated from the ethanolic extract. Compound 3 exhibited the strongest activity against KKU-M156 cell line (IC50 = 8.14 ± 1.15 µg/ml), but 1 and 2 showed no cytotoxic activity (IC50 > 100 µg/ml). In conclusion, quercetin showed the highest efficacy against cholangiocarcinoma. These results support the traditional use of this plant by Thai traditional doctors for cancer treatment.

Keywords: cholangiocarcinoma, cytotoxicity, flavonoid, Smilax corbularia

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Authors: Belkis L. Cabrera

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Contemporary technological innovations have reshaped possibility, interaction, communication, engagement, education, and training. Indeed, today, a high-quality technology enhanced learning experience can be transformative as much for the learner as for the educator-trainer. As innovative technologies continue to facilitate, support, foster, and enhance collaboration, problem-solving, creativity, adaptiveness, multidisciplinarity, and communication, the field of instructional design (ID) also continues to develop and expand. Shifting its focus from media to the systematic design of instruction, or rather from the gadgets and devices themselves to the theories, models, and impact of implementing educational technology, the evolution of ID marks a restructuring of the teaching, learning, and training paradigms. However, with all of its promise, this latter component of ID remains underdeveloped. The majority of ID models are crafted and guided by learning theories and, therefore, most models are constructed around student and educator roles rather than trainer roles. Thus, when these models or systems are employed for training purposes, they usually have to be re-fitted, tweaked, and stretched to meet the training needs. This paper is concerned with the training or professional development (PD) facet of instructional design and how ID models built on teacher-to-teacher interaction and dialogue can support the creation of professional learning communities (PLCs) or communities of practice (CoPs), which can augment learning and PD experiences for all. Just as technology is changing the face of education, so too can it change the face of PD within the educational realm. This paper not only provides a new ID model but using innovative technologies such as Padlet and Thinkbinder, this paper presents a concrete example of how a traditional body-to-body, brick, and mortar learning community can be transferred and transformed into the online context.

Keywords: communities of practice, e-learning, educational reform, instructional design, professional development, professional learning communities, technology, training

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Authors: Youngjae Jin, Daeshik Kim

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This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning

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Authors: H. Alqunayeer, S. Zamir

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Blended learning, an ideal amalgamation of online learning and face to face traditional approach is a new approach that may result in outstanding outcomes in the realm of teaching and learning. The dexterity and effectiveness offered by e-learning experience cannot be guaranteed in a traditional classroom, whereas one-to-one interaction the essential element of learning that can only be found in a traditional classroom. In recent years, a spectacular expansion in the incorporation of technology in language teaching and learning is observed in many universities of Saudi Arabia. Some universities recognize the importance of blending face-to-face with online instruction in language pedagogy, Qassim University is one of the many universities adopting Blackboard Learning Management system (LMS). The university has adopted this new mode of teaching/learning in year 2015. Although the experience is immature; however great pedagogical transformations are anticipated in the university through this new approach. This paper examines the role of blended language learning with particular reference to the influence of Blackboard Learning Management System on the development of English language learning for EFL learners registered in Bachelors of English language program. This paper aims at exploring three main areas: (i) the present status of Blended learning in the educational process in Saudi Arabia especially in Qassim University by providing a survey report on the number of training courses on Blackboard LMS conducted for the male and female teachers at various colleges of Qassim University, (ii) a survey on teachers perception about the utility, application and the outcome of using blended Learning approach in teaching English language skills courses, (iii) the students’ views on the efficiency of Blended learning approach in learning English language skills courses. Besides, analysis of students’ limitations and challenges related to the experience of blended learning via Blackboard, the suggestion and recommendations offered by the language learners have also been thought-out. The study is empirical in nature. In order to gather data on the afore mentioned areas survey questionnaire method has been used: in order to study students’ perception, a 5 point Likert-scale questionnaire has been distributed to 200 students of English department registered in Bachelors in English program (level 5 through level 8). Teachers’ views have been surveyed with the help of interviewing 25 EFL teachers skilled in using Blackboard LMS in their lectures. In order to ensure the validity and reliability of questionnaire, the inter-rater approach and Cronbach’s Alpha analysis have been used respectively. Analysis of variance (ANOVA) has been used to analyze the students’ perception about the productivity of the Blended approach in learning English language skills. The analysis of feedback by Saudi teachers and students about the usefulness, ingenuity, and productivity of Blended Learning via Blackboard LMS highlights the need of encouraging and expanding the implementation of this new approach into the field of English language teaching in Saudi Arabia, in order to augment congenial learning aura. Furthermore, it is hoped that the propositions and practical suggestions offered by the study will be functional for other similar learning environments.

Keywords: blended learning, black board learning management system, English as foreign language (EFL) learners, EFL teachers

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Authors: Alexander Vandesompele, Joni Dambre

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The diversity in dendritic arborization, as first illustrated by Santiago Ramon y Cajal, has always suggested a role for dendrites in the functionality of neurons. In the past decades, thanks to new recording techniques and optical stimulation methods, it has become clear that dendrites are not merely passive electrical components. They are observed to integrate inputs in a non-linear fashion and actively participate in computations. Regardless, in simulations of neural networks dendritic structure and functionality are often overlooked. Especially in a machine learning context, when designing artificial neural networks, point neuron models such as the leaky-integrate-and-fire (LIF) model are dominant. These models mimic the integration of inputs at the neuron soma, and ignore the existence of dendrites. In this work, the LIF point neuron model is extended with a simple form of dendritic computation. This gives the LIF neuron increased capacity to discriminate spatiotemporal input sequences, a dendritic functionality as observed in another study. Simulations of the spiking neurons are performed using the Bindsnet framework. In the common LIF model, incoming synapses are independent. Here, we introduce a dependency between incoming synapses such that the post-synaptic impact of a spike is not only determined by the weight of the synapse, but also by the activity of other synapses. This is a form of short term plasticity where synapses are potentiated or depressed by the preceding activity of neighbouring synapses. This is a straightforward way to prevent inputs from simply summing linearly at the soma. To implement this, each pair of synapses on a neuron is assigned a variable,representing the synaptic relation. This variable determines the magnitude ofthe short term plasticity. These variables can be chosen randomly or, more interestingly, can be learned using a form of Hebbian learning. We use Spike-Time-Dependent-Plasticity (STDP), commonly used to learn synaptic strength magnitudes. If all neurons in a layer receive the same input, they tend to learn the same through STDP. Adding inhibitory connections between the neurons creates a winner-take-all (WTA) network. This causes the different neurons to learn different input sequences. To illustrate the impact of the proposed dendritic mechanism, even without learning, we attach five input neurons to two output neurons. One output neuron isa regular LIF neuron, the other output neuron is a LIF neuron with dendritic relationships. Then, the five input neurons are allowed to fire in a particular order. The membrane potentials are reset and subsequently the five input neurons are fired in the reversed order. As the regular LIF neuron linearly integrates its inputs at the soma, the membrane potential response to both sequences is similar in magnitude. In the other output neuron, due to the dendritic mechanism, the membrane potential response is different for both sequences. Hence, the dendritic mechanism improves the neuron’s capacity for discriminating spa-tiotemporal sequences. Dendritic computations improve LIF neurons even if the relationships between synapses are established randomly. Ideally however, a learning rule is used to improve the dendritic relationships based on input data. It is possible to learn synaptic strength with STDP, to make a neuron more sensitive to its input. Similarly, it is possible to learn dendritic relationships with STDP, to make the neuron more sensitive to spatiotemporal input sequences. Feeding structured data to a WTA network with dendritic computation leads to a significantly higher number of discriminated input patterns. Without the dendritic computation, output neurons are less specific and may, for instance, be activated by a sequence in reverse order.

Keywords: dendritic computation, spiking neural networks, point neuron model

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Authors: Mohamed Chabi

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The purpose of this study is to determine Whether paper assessment especially in the subject mathematics will ever be completely replaced by online assessment using Learning Management System and Content Management System such as blackboard. In the subject mathematics, the assessment is the exercise of judgment on the quality of students’ work, as a way of supporting student learning and appraising its outcomes. Testing students has moved from the traditional scribbling and sketching on paper towards working online on a screen and keyboard.

Keywords: paper assessment, online assessment, learning management system, content management system, mathematics

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Authors: Abdulwakeel B. Raji

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This paper introduces a concept of an intelligent virtual learning environment that involves communication between learners and an artificially intelligent teaching agent in an attempt to replicate classroom learning interactions. The benefits of this technology over current e-learning practices is that it creates a virtual classroom where real time adaptive learning interactions are made possible. This is a move away from the static learning practices currently being adopted by e-learning systems. Over the years, artificial intelligence has been applied to various fields, including and not limited to medicine, military applications, psychology, marketing etc. The purpose of e-learning applications is to ensure users are able to learn outside of the classroom, but a major limitation has been the inability to fully replicate classroom interactions between teacher and students. This study used comparative surveys to gain information and understanding of the current learning practices in Nigerian universities and how they compare to these practices compare to the use of a developed e-learning system. The study was conducted by attending several lectures and noting the interactions between lecturers and tutors and as an aftermath, a software has been developed that deploys the use of an artificial intelligent teaching-agent alongside an e-learning system to enhance user learning experience and attempt to create the similar learning interactions to those found in classroom and lecture hall settings. Dialogflow has been used to implement a teaching-agent, which has been developed using JSON, which serves as a virtual teacher. Course content has been created using HTML, CSS, PHP and JAVASCRIPT as a web-based application. This technology can run on handheld devices and Google based home technologies to give learners an access to the teaching agent at any time. This technology also implements the use of definite clause grammars and natural language processing to match user inputs and requests with defined rules to replicate learning interactions. This technology developed covers familiar classroom scenarios such as answering users’ questions, asking ‘do you understand’ at regular intervals and answering subsequent requests, taking advanced user queries to give feedbacks at other periods. This software technology uses deep learning techniques to learn user interactions and patterns to subsequently enhance user learning experience. A system testing has been undergone by undergraduate students in the UK and Nigeria on the course ‘Introduction to Database Development’. Test results and feedback from users shows that this study and developed software is a significant improvement on existing e-learning systems. Further experiments are to be run using the software with different students and more course contents.

Keywords: virtual learning, natural language processing, definite clause grammars, deep learning, artificial intelligence

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Authors: Rajesh Ranjan, Marimuthu Palaniswami, A. A. Hashmi

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With the changing lifestyle and environment around us, the prevalence of the critical and incurable disease has proliferated. One such condition is the neurological disorder which is rampant among the old age population and is increasing at an unstoppable rate. Most of the neurological disorder patients suffer from some movement disorder affecting the movement of their body parts. Tremor is the most common movement disorder which is prevalent in such patients that infect the upper or lower limbs or both extremities. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor (essential tremor). The patients suffering from tremor face enormous trouble in performing the daily activity, and they always need a caretaker for assistance. In the clinics, the assessment of tremor is done through a manual clinical rating task such as Unified Parkinson’s disease rating scale which is time taking and cumbersome. Neurologists have also affirmed a challenge in differentiating a Parkinsonian tremor with the pure tremor which is essential in providing an accurate diagnosis. Therefore, there is a need to develop a monitoring and assistive tool for the tremor patient that keep on checking their health condition by coordinating them with the clinicians and caretakers for early diagnosis and assistance in performing the daily activity. In our research, we focus on developing a system for automatic classification of tremor which can accurately differentiate the pure tremor from the Parkinsonian tremor using a wearable accelerometer-based device, so that adequate diagnosis can be provided to the correct patient. In this research, a study was conducted in the neuro-clinic to assess the upper wrist movement of the patient suffering from Pure (Essential) tremor and Parkinsonian tremor using a wearable accelerometer-based device. Four tasks were designed in accordance with Unified Parkinson’s disease motor rating scale which is used to assess the rest, postural, intentional and action tremor in such patient. Various features such as time-frequency domain, wavelet-based and fast-Fourier transform based cross-correlation were extracted from the tri-axial signal which was used as input feature vector space for the different supervised and unsupervised learning tools for quantification of severity of tremor. A minimum covariance maximum correlation energy comparison index was also developed which was used as the input feature for various classification tools for distinguishing the PT and ET tremor types. An automatic system for efficient classification of tremor was developed using feature extraction methods, and superior performance was achieved using K-nearest neighbors and Support Vector Machine classifiers respectively.

Keywords: machine learning approach for neurological disorder assessment, automatic classification of tremor types, feature extraction method for tremor classification, neurological movement disorder, parkinsonian tremor, essential tremor

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Authors: Hamdi Belfeki, Belgacem Chandoul, Mnasser Hassouna, Mondher Mejri

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Aqueous and ethanolic extracts of eight Tunisian aromatic and medicinal plants (TAMP) were characterized by studying their composition in polyphenols and also their antiradical and antioxidant capacities. In absence and in the presence of the various extracts, α-amylase from Bacillus subtlis activity, was measured in order to detect a potential inhibition. The total contents of polyphenols and flavonoid vary in function of TAMP and the mobile phase used for the extraction (distilled water or ethanol). The ethanolic extracts showed the most significant antiradical and antioxidant activities. Only the extracts from Coriandrum sativum showed a significant inhibiting effect on the α-amylase activity. This inhibiting capacity could be correlated with the chemical profile of the two extracts, due to the fact that they have the greatest amount of total flavonoid. The ethanolic extract has the most important antioxidant and anti-radicalizing activities among the sixteen extracts studied. The inhibition kinetics of the two coriander extracts were evaluated by pre-incubation method, using Lineweaver-Burk’s equation, obtained by linearization of Michaeilis-Menten’s expression. The results showed that both extracts exercised a competitive inhibition mechanism.

Keywords: α-amylase, antioxidant activity, aromatic and medicinal plants, inhibition

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Authors: Felermino D. M. A. Ali, S. C. Ng

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E-learning is an evolutionary form of distance learning and has become better over time as new technologies emerged. Today, efforts are still being made to embrace E-learning systems with emerging technologies in order to make them better. Among these advancements, Educational Data Mining (EDM) is one that is gaining a huge and increasing popularity due to its wide application for improving the teaching-learning process in online practices. However, even though EDM promises to bring many benefits to educational industry in general and E-learning environments in particular, its principal drawback is the lack of easy to use tools. The current EDM tools usually require users to have some additional technical expertise to effectively perform EDM tasks. Thus, in response to these limitations, this study intends to design and implement an EDM application framework which aims at automating and simplify the development of EDM in E-learning environment. The application framework introduces a Service-Oriented Architecture (SOA) that hides the complexity of technical details and enables users to perform EDM in an automated fashion. The framework was designed based on abstraction, extensibility, and interoperability principles. The framework implementation was made up of three major modules. The first module provides an abstraction for data gathering, which was done by extending Moodle LMS (Learning Management System) source code. The second module provides data mining methods and techniques as services; it was done by converting Weka API into a set of Web services. The third module acts as an intermediary between the first two modules, it contains a user-friendly interface that allows dynamically locating data provider services, and running knowledge discovery tasks on data mining services. An experiment was conducted to evaluate the overhead of the proposed framework through a combination of simulation and implementation. The experiments have shown that the overhead introduced by the SOA mechanism is relatively small, therefore, it has been concluded that a service-oriented architecture can be effectively used to facilitate educational data mining in E-learning environments.

Keywords: educational data mining, e-learning, distributed data mining, moodle, service-oriented architecture, Weka

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Authors: John Olav Bjornestad, Bjorn Tore Johansen

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The number of people suffering from mental illnesses is increasing, and such illness is currently one of the major causes of disability and poor health. The reason for this is most likely a lack of physical activity. The purpose of this study was to discover if physical activity was an effective mode of treatment for psychiatric patients at an out-patient treatment facility. The study included an exploration of whether or not patients having physical activity included as an integral part of their treatment (to a greater degree than do patients who are physically inactive) would achieve 1) an improvement in their physical condition 2) a reduction in symptomatic pressure and 3) an increase in their health-related quality of life. The intervention period lasted a total of 12 weeks. The training group completed a minimum of 2 training sessions per week with an intensity of 60-75% of maximum heart rate. The participants’ health-related quality of life (SF-36), symptomatic pressure (SCL-90-R) and physical condition (UKK-walking test) were measured before and after intervention. Twenty participants were pre-tested, and out of this initial group, nine patients completed the intervention program and participated thereafter in post-testing. The results showed that participants on average improved their physical condition, reduced their symptomatic pressure and increased their health-related quality of life over the course of the intervention period. The training group experienced significant changes in their symptomatic pressure (the anxiety dimension) and health-related quality of life (the mental health dimension) from the pre-testing stage to the post-testing one. Furthermore, there was a significant connection between symptomatic pressure and health-related quality of life. The patients who were admitted to the psychiatric out-patient clinic were in a physical condition that was significantly poorer than that of persons of the same age in the remainder of the population. Experiences from the study and the relatively large defection from it demonstrate that there is a great need for close follow-up of psychiatric patients’ physical activity levels when physical activity and lifestyle changes are included as part of their treatment program.

Keywords: health-related quality, mental health, physical activity, physical condition

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Authors: Ikram Mohamed Eltayeb, Ustina Saeed Barsoumbolice

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Cinnamomum zeylanicum belong to the family Lauraceae and Artemisia absinthium belong to the family Asteraceae. Both were traditionally used as antiemetic, anti-inflammatory and antidiabetic. In Sudan, the mixtures of the two plants were traditionally used for the treatment of diabetes. Diabetes mellitus is a group of metabolic diseases characterized by hyperglycemia. It is mainly classified into two major groups, type-1 and type-2. Type-2 is a combination of resistance to insulin action and an inadequate compensatory insulin secretory response. The treatment of type-2 diabetes mellitus (DM) with synthetic drugs have many side effects so many researches were conducted to overcome or reduce this side effects by using alternative medicine. The objective of this study is to investigate and compare the anti-diabetic activity of C. zeylanicum and A. absinthium and their combination with difference ratio. C. zeylanicum and A. absinthium were extracted by 96% ethanol using Soxhlet apparatus. Thirty-two rats were divided into eight groups; each group contains four rats. 1st group was administered with distilled water at dose of 10ml/kg, 2nd group had received glucose only at dose of 2g/kg intraperitoneal, the standard group (3rd group) had received Glibenclamide orally at dose of 0.45mg/kg, 4th group received 100 mg C. zeylanicum + 300 mg A. absinthium with a ratio of (25:75), 5th group received 300 mg C. zeylanicum + 100 mg A. absinthium with a ratio of (75:25), 6th group received 200 mg C. zeylanicum + 200 mg A. absinthiumwith a ratio of (50:50), 7th group received 400 mg of A. absinthium, 8th group received 400 mg of C. zeylanicum. Then the blood samples were taken Retro-orbitally at 0, 1, 2 and 4 hours and the glucose level was measured. Each plant alone and their combination with different ratios shows antidiabetic effect. The significant activity was shown by A. absinthium extract (400 mg/kg), combination of ratio of (75:25) A. absinthium: C. zeylanicum(400mg/kg) and then C. zeylanicum(400mg/kg) with p-value 0.001, 0.022, 0.030 respectively, the activity was found to be increased with time. The other combinations showed less activity with p-value > 0.05. The result concludes that the good antidiabetic activity was performed by A. absinthium alone and its activity decreased by increase combination ratio with C. zeylanicum. Which maybe explains by the antagonistic effect between the compounds of C. zeylanicum and A. absinthium.

Keywords: antidiabetic, Artemisia absinthium , cinnamomum zeylanicum, combination

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Authors: V. Vargas-Alejo, L. E. Montero-Moguel

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Understanding the concept of function has been important in mathematics education for many years. In this study, the models built by a group of five business administration and accounting undergraduate students when carrying out a population growth activity are analyzed. The theoretical framework is the Models and Modeling Perspective. The results show how the students included tables, graphics, and algebraic representations in their models. Using technology was useful to interpret, describe, and predict the situation. The first model, the students built to describe the situation, was linear. After that, they modified and refined their ways of thinking; finally, they created exponential growth. Modeling the activity was useful to deep on mathematical concepts such as covariation, rate of change, and exponential function also to differentiate between linear and exponential growth.

Keywords: covariation reasoning, exponential function, modeling, representations

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Authors: Chen Wang, Gerard Rowe

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The number of undergraduate engineering students enrolled in university has been increasing rapidly recently, leading to challenges associated with increased student-instructor ratios and increased diversity in academic preparedness of the entrants. An increased student-instructor ratio makes the interaction between teachers and students more difficult, with the resulting student ‘anonymity’ known to be a risk to academic success. With increasing student numbers, there is also an increasing diversity in the academic preparedness of the students at entry to university. Conceptual understanding of the entrants has been quantified via diagnostic testing, with the results for the first-year course in electrical engineering showing significant conceptual misunderstandings amongst the entry cohort. The solution is clearly multi-faceted, but part of the solution likely involves greater demands being placed on students to be masters of their own learning. In consequence, it is highly desirable that instructors help students to develop better self-regulated learning skills. A self-regulated learner is one who is capable of setting up their own learning goals, monitoring their study processes, adopting and adjusting learning strategies, and reflecting on their own study achievements. The methods by which instructors might cultivate students’ self-regulated learning abilities is receiving increasing attention from instructors and researchers. The aim of this study was to help students understand fully their self-regulated learning skill levels and provide targeted instructions to help them improve particular learning abilities in order to meet the curriculum requirements. As a survey tool, this research applied the questionnaire ‘Motivated Strategies for Learning Questionnaire’ (MSLQ) to collect first year engineering student’s self-reported data of their cognitive abilities, motivational orientations and learning strategies. MSLQ is a widely-used questionnaire for assessment of university student’s self-regulated learning skills. The questionnaire was offered online as a part of the online-scaffolding-learning tools to develop student understanding of self-regulated learning theories and learning strategies. The online tools, which have been under development since 2015, are designed to help first-year students understand their self-regulated learning skill levels by providing prompt feedback after they complete the questionnaire. In addition, the online tool also supplies corresponding learning strategies to students if they want to improve specific learning skills. A total of 866 first year engineering students who enrolled in the first-year electrical engineering course were invited to participate in this research project. By the end of the course 857 students responded and 738 of their questionnaires were considered as valid questionnaires. Analysis of these surveys showed that 66% of the students thought the online-scaffolding-learning tools helped significantly to improve their self-regulated learning abilities. It was particularly pleasing that 16.4% of the respondents thought the online-scaffolding-learning tools were extremely effective. A current thrust of our research is to investigate the relationships between students’ self-regulated learning abilities and their academic performance. Our results are being used by the course instructors as they revise the curriculum and pedagogy for this fundamental first-year engineering course, but the general principles we have identified are applicable to most first-year STEM courses.

Keywords: academic preparedness, online-scaffolding-learning tool, self-regulated learning, STEM education

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Authors: Sanjeeb Kumar Mohanty

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Content Based Instruction (CBI) in English Language Teaching (ELT) basically helps English as Second Language (ESL) learners of English. At the same time, it fosters multidisciplinary style of learning by promoting collaborative learning style. It is an approach to teaching ESL that attempts to combine language with interdisciplinary learning for bettering language proficiency and facilitating content learning. Hence, the basic purpose of CBI is that language should be taught in conjunction with academic subject matter. It helps in establishing the content as well as developing language competency. This study aims at supporting the potential values of interdisciplinary approach in promoting English Language Learning (ELL) by teaching writing skills to a small group of learners and discussing the findings with the teachers from various disciplines in a workshop. The teachers who are oriented, they use the same approach in their classes collaboratively. The inputs from the learners as well as the teachers hopefully raise positive consciousness with regard to the vast benefits that Content Based Instruction can offer in advancing the language competence of the learners.

Keywords: content based instruction, interdisciplinary approach, writing skills, collaborative approach

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Authors: Silvia Gastaldello, Maria Grillo, Luca Tassoni, Claudio Maran, Stefano Balbo

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Antioxidants are nowadays attractive not only for the countless benefits to the human and animal health, but also for the perspective of use as food preservative instead of synthetic chemical molecules. In this study, the radical scavenging activity of six protein extracts from pulse and oleaginous seeds was evaluated. The selected matrices are Pisum sativum (yellow pea from two different origins), Carthamus tinctorius (safflower), Helianthus annuus (sunflower), Lupinus luteus cv Mister (lupin) and Glycine max (soybean), since they are economically interesting for both human and animal nutrition. The seeds were grinded and proteins extracted from 20mg powder with a specific vegetal-extraction kit. Proteins have been quantified through Bradford protocol and scavenging activity was revealed using DPPH assay, based on radical DPPH (2,2-diphenyl-1-picrylhydrazyl) absorbance decrease in the presence of antioxidants molecules. Different concentrations of the protein extract (1, 5, 10, 50, 100, 500 µg/ml) were mixed with DPPH solution (DPPH 0,004% in ethanol 70% v/v). Ascorbic acid was used as a scavenging activity standard reference, at the same six concentrations of protein extracts, while DPPH solution was used as control. Samples and standard were prepared in triplicate and incubated for 30 minutes in dark at room temperature, the absorbance was read at 517nm (ABS30). Average and standard deviation of absorbance values were calculated for each concentration of samples and standard. Statistical analysis using t-students and p-value were performed to assess the statistical significance of the scavenging activity difference between the samples (or standard) and control (ABSctrl). The percentage of antioxidant activity has been calculated using the formula [(ABSctrl-ABS30)/ABSctrl]*100. The obtained results demonstrate that all matrices showed antioxidant activity. Ascorbic acid, used as standard, exhibits a 96% scavenging activity at the concentration of 500 µg/ml. At the same conditions, sunflower, safflower and yellow peas revealed the highest antioxidant performance among the matrices analyzed, with an activity of 74%, 68% and 70% respectively (p < 0.005). Although lupin and soybean exhibit a lower antioxidant activity compared to the other matrices, they showed a percentage of 46 and 36 respectively. All these data suggest the possibility to use undervalued edible matrices as antioxidants source. However, further studies are necessary to investigate a possible synergic effect of several matrices as well as the impact of industrial processes for a large-scale approach.

Keywords: antioxidants, DPPH assay, natural matrices, vegetal proteins

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Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

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Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

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Authors: Vasiliki Stratidou

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Modern simulation mobile games have the potential to enhance students’ interest, motivation and creativity. Research conducted on the effectiveness of digital games for educational purposes has shown that such games are also ideal at providing an appropriate environment for language learning. The paper examines the issue of simulation mobile games in regard to the potential positive impacts on L2 vocabulary learning. Sixteen intermediate level students, aged 10-14, participated in the experimental study for four weeks. The participants were divided into experimental (8 participants) and control group (8 participants). The experimental group was planned to learn some new vocabulary words via digital games while the control group used a reading passage to learn the same vocabulary words. The study investigated the effect of mobile games as well as the traditional learning methods on Greek EFL learners’ vocabulary learning in a pre-test, an immediate post-test, and a two-week delayed retention test. A teacher’s diary and learners’ interviews were also used as tools to estimate the effectiveness of the implementation. The findings indicated that the experimental group outperformed the control group in acquiring new words through mobile games. Therefore, digital games proved to be an effective tool in learning English vocabulary.

Keywords: control group, digital games, experimental group, second language vocabulary learning, simulation games

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Authors: Luis Miguel Méndez Díaz

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In this article, a mathematics teaching-learning strategy will be presented, specifically differential calculus in one variable, in a fun and competitive space in which the action on the part of the student is manifested and not only the repetition of information on the part of the teacher. Said action refers to motivating, problematizing, summarizing, and coordinating a game of dominoes whose thematic cards are designed around the basic and main contents of differential calculus. The strategies for teaching this area are diverse and precisely the game of dominoes is one of the most used strategies in the practice of mathematics because it stimulates logical reasoning and mental abilities. The objective on this investigation is to identify the way in which the game of dominoes affects the learning and understanding of fundamentals concepts of differential calculus in one variable through experimentation carried out on students of the first semester of the School of Engineering and Sciences of the Technological Institute of Monterrey Campus Querétaro. Finally, the results of this study will be presented and the use of this strategy in other topics around mathematics will be recommended to facilitate logical and meaningful learning in students.

Keywords: collaborative learning, logical-mathematical intelligence, mathematical games, multiple intelligences

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Authors: Dong Xie, Leah Howard, Yiming Weng

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The objective of this study was to synthesize and characterize 5-acryloyloxy-3,4-dichlorocrotonolactone (a furanone derivative), use this derivative to modify a dental restorative, and study the effect of the derivative on the antibacterial activity and compressive strength of the formed restorative. In this study, a furanone derivative was synthesized, characterized, and used to formulate a dental restorative. Compressive strength (CS) and S. mutans viability were used to evaluate the mechanical strength and antibacterial activity of the formed restorative. The fabricated restorative specimens were photocured and conditioned in distilled water at 37oC for 24 h, followed by direct testing for CS or/and incubating with S. mutans for 48 h for antibacterial testing. The results show that the modified dental restorative showed a significant antibacterial activity without substantially decreasing the mechanical strengths. With addition of the antibacterial derivative up to 30%, the restorative kept its original CS nearly unchanged but showed a significant antibacterial activity with 68% reduction in the S. mutans viability. Furthermore, the antibacterial function of the modified restorative was not affected by human saliva. The aging study also indicates that the modified restorative may have a long-lasting antibacterial function. It is concluded that this experimental antibacterial restorative may potentially be developed into a clinically attractive dental filling restorative due to its high mechanical strength and antibacterial function.

Keywords: antibacterial, dental restorative, compressive strength, S. mutans viability

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Authors: Asif Husain, Shah Alam Khan

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Coumarins and flavones are oxygen containing heterocyclic compounds which are present in various biologically active compounds. Both the heterocyclic rings are associated with diverse biological actions, therefore considered as an important scaffold for the design of molecules of pharmaceutical interest. Aim: To synthesize and evaluate the in vivo anti-inflammatory activity of few coumrain and flavone derivatives containing 1,4 dioxane ring system. Materials and methods: Coumarin derivatives (3a-d) were synthesized by reacting 7,8 dihydroxy coumarin (2a) and its 4-methyl derivative (2b) with epichlorohydrin/ethylene dibromide. The flavone derivatives (10a-d) were prepared by using quercetin and 3,4 dihydroxy flavones. Compounds of both the series were also evaluated for their anti-inflammatory, analgesic activity and ulcerogenicity in animal models by reported methods. Results and Discussion: The structures of all newly synthesized compounds were confirmed with the help of IR, 1H NMR, 13C NMR and Mass spectral studies. Elemental analyses data for each element analyzed (C, H, N) was found to be within acceptable range of ±0.4 %. Flavone derivatives, but in particular quercetin containing 1,4 dioxane ring system (10d) showed better anti-inflammatory and analgesic activity along with reduced gastrointestinal toxicity as compared to other synthesized compounds. The results of anti-inflammatory and analgesic activities of both the series are comparable with the positive control, diclofenac. Conclusion: Compound 10d, a quercetin derivative, emerged as a lead molecule which exhibited potent anti-inflammatory and analgesic activity with significant reduced gastric toxicity.

Keywords: analgesic, anti-inflammatory, 1, 4 dioxane, coumarin, flavone

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Authors: Mohamed Elhadi M. Sharif, Mona Masood

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The usage of e-health facilities is seen to be the first priority by the Libyan government. As such, this paper focuses on how the key factors or elements of working size in terms of technological availability, structural environment, and other competence-related matters may affect nurses’ sharing of knowledge in e-health. Hence, this paper investigates learning readiness assessment to raise e-health for Libyan regional hospitals by using e-health services in nursing education.

Keywords: Libyan nurses, e-learning readiness, e-health, nursing education

Procedia PDF Downloads 474