Search results for: chemical learning

Authors: Jimmy K. C. Lam, Carrie Wong

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One of the key goals on Learning and Teaching as documented in the University strategic plan 2012/13 – 2017/18 is to encourage active learning, the use of innovative teaching approaches and technology, and promoting the adoption of flexible and varied teaching delivery methods. This research reported the recent visited to Prof Eric Mazur at Harvard University on Peer Instruction: Collaborative learning in large class and innovative use of technology to enable new mode of learning. Peer Instruction is a research-based, interactive teaching method developed by Prof. Eric Mazur at Harvard University in the 1990s. It has been adopted across the disciplines, institutional type and throughout the world. One problem with conventional teaching lies in the presentation of the material. Frequently, it comes straight out of textbook/notes, giving students little incentive to attend class. This traditional presentation is always delivered as monologue in front of passive audience. Only exceptional lecturers are capable of holding students’ attention for an entire lecture period. Consequently, lectures simply reinforce students’ feelings that the most important step in mastering the material is memorizing a zoo of unrelated examples. In order to address these misconceptions about learning, Prof Mazur’s Team developed “Peer Instruction”, a method which involves students in their own learning during lectures and focuses their attention on underling concepts. Lectures are interspersed with conceptual questions called Concept Tests, designed to expose common difficulties in understanding the material. The students are given one or two minutes to think about the question and formulate their own answers; they then spend two or three minutes discussing their answers in a group of three or four, attempting to reach consensus on the correct answer. This process forces the students to think through the arguments being developed, and enable them to assess their understanding concepts before they leave the classroom. The findings from Peer Instruction and innovative use of technology on teaching at Harvard University were applied to the first year Textiles and Fashion students in Hong Kong. Survey conducted from 100 students showed that over 80% students enjoyed the flexibility of peer instruction and 70% of them enjoyed the instant feedback from the Clicker system (Student Response System used at Harvard University). Further work will continue to explore the possibility of peer instruction to art and fashion students.

Keywords: peer instruction, education, technology, fashion

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Authors: Abbas Hadj Abbas, Hacini Massaoud, Aiad Lahcen

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In Hassi-Messoud’s oil industry, the systems which are water based (WBM) are generally used for drilling in the first phase. For the rest of the well, the oil mud systems are employed (OBM). In the field of oil exploration, panoply of chemical products is employed in the drilling fluids formulation. These components of different natures and whose toxicity and biodegradability are of ill-defined parameters are; however, thrown into nature. In addition to the hydrocarbon (HC, such as diesel) which is a major constituent of oil based mud, we also can notice spills as well as a variety of other products and additives on the drilling sites. These wastes are usually stored in places called (crud wastes). These may cause major problems to the ecosystem. To treat these wastes, we have considered two methods which are: solidification/ stabilization (chemical) and thermal. So that we can evaluate the techniques of treatment, a series of analyses are performed on dozens of specimens of wastes before treatment. After that, and on the basis of our analyses of wastes, we opted for diagnostic treatments of pollution before and after solidification and stabilization. Finally, we have done some analyses before and after the thermal treatment to check the efficiency of the methods followed in the study.

Keywords: wastes treatment, the oil pollution, the norms, wastes drilling

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Authors: Yaling Gou, Sucai Yang, Pengwei Qiao

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Integrated chemical-biological treatment is an attractive alternative to remove polycyclic aromatic hydrocarbons (PAHs) from contaminated soil; wherein indigenous bacteria is the key factor for the biodegradation of residual PAHs concentrations after the application of chemical oxidation. However, the systematical study on the impact of persulfate (PS) oxidation on indigenous bacteria as well as PAHs removal is still scarce. In this study, the influences of different PS dosages (1%, 3%, 6%, and 10% [w/w]), as well as various activation methods (native iron, H2O2, alkaline, ferrous iron, and heat) on PAHs removal and indigenous bacteria in highly contaminated aged soil were investigated. Apparent degradation of PAHs in the soil treated with PS oxidation was observed, and the removal efficiency of total PAHs in the soil ranged from 38.28% to 79.97%. The removal efficiency of total PAHs in the soil increased with increasing consumption of PS. However, the bacterial abundance in soil was negatively affected following oxidation for all of the treatments added with PS, with bacterial abundance in the soil decreased by 0.89~2.88 orders of magnitude compared to the untreated soil. Moreover, the number of total bacteria in the soil decreased as PS consumption increased. Different PS activation methods and PS dosages exhibited different influences on the bacterial community composition. Bacteria capable of degrading PAHs under anoxic conditions were composed predominantly by Proteobacteria and Firmicutes. The total amount of Proteobacteria and Firmicutes also decreased with increasing consumption of PS. The results of this study provide important insight into the design of PAHs contaminated soil remediation projects.

Keywords: activation method, chemical oxidation, indigenous bacteria, polycyclic aromatic hydrocarbon

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Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: Zhiyong Zheng, Xu Li, Liang Huang, Zhengliang Sun, Jianhua Xu

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Yaw angle plays a significant role in many vehicle safety applications, such as collision avoidance and lane-keeping system. Although the estimation of the yaw angle has been extensively studied in existing literature, it is still the main challenge to simultaneously achieve a reliable and cost-effective solution in complex urban environments. This paper proposes a multi-stage learning framework to estimate the yaw angle with a monocular camera, which can deal with the challenge in a more reliable manner. In the first stage, an efficient road detection network is designed to extract the road region, providing a highly reliable reference for the estimation. In the second stage, a variational auto-encoder (VAE) is proposed to learn the distribution patterns of road regions, which is particularly suitable for modeling the changing patterns of yaw angle under different driving maneuvers, and it can inherently enhance the generalization ability. In the last stage, a gated recurrent unit (GRU) network is used to capture the temporal correlations of the learned patterns, which is capable to further improve the estimation accuracy due to the fact that the changes of deflection angle are relatively easier to recognize among continuous frames. Afterward, the yaw angle can be obtained by combining the estimated deflection angle and the road direction stored in a roadway map. Through effective multi-stage learning, the proposed framework presents high reliability while it maintains better accuracy. Road-test experiments with different driving maneuvers were performed in complex urban environments, and the results validate the effectiveness of the proposed framework.

Keywords: gated recurrent unit, multi-stage learning, reliable estimation, variational auto-encoder, yaw angle

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Authors: Rahimah Akbar, Abdullah Al-Hashemi, Hanan Taqi, Taiba Sadeq

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As technology continues to develop, teaching curriculums in both schools and universities have begun adopting a more computer/digital based approach to the transmission of knowledge and information, as opposed to the more old-fashioned use of textbooks. This gives rise to the question: Are there any differences in learning from a digital source over learning from a printed source, as in from a textbook? More specifically, which medium of information results in better long-term retention? A review of the confounding factors implicated in understanding the relationship between learning from the two different mediums was done. Alongside this, a 4-week cohort study involving 76 1st year English Language female students was performed, whereby the participants were divided into 2 groups. Group A studied material from a paper source (referred to as the Print Medium), and Group B studied material from a digital source (Digital Medium). The dependent variables were grading of memory recall indexed by a 4 point grading system, and total frequency of item repetition. The study was facilitated by advanced computer software called Super Memo. Results showed that, contrary to prevailing evidence, the Digital Medium group showed no statistically significant differences in terms of the shift from Remember (Episodic) to Know (Semantic) when all confounding factors were accounted for. The shift from Random Guess and Familiar to Remember occurred faster in the Digital Medium than it did in the Print Medium.

Keywords: digital medium, print medium, long-term memory recall, episodic memory, semantic memory, super memo, forgetting index, frequency of repetitions, total time spent

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Authors: Breno Barrreto Silva, Agnieszka Otwinowska, Katarzyna Kutylowska

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Research comparing lexical learning following the writing of sentences and longer texts with keywords is limited and contradictory. One possibility is that the recursivity of writing may enhance processing and increase lexical learning; another possibility is that the higher cognitive load of complex-text writing (e.g., essays), at least when timed, may hinder the learning of words. In our study, we selected 2 sets of 10 academic keywords matched for part of speech, length (number of characters), frequency (SUBTLEXus), and concreteness, and we asked 90 L1-Polish advanced-level English majors to use the keywords when writing sentences, timed (60 minutes) or untimed essays. First, all participants wrote a timed Control essay (60 minutes) without keywords. Then different groups produced Timed essays (60 minutes; n=33), Untimed essays (n=24), or Sentences (n=33) using the two sets of glossed keywords (counterbalanced). The comparability of the participants in the three groups was ensured by matching them for proficiency in English (LexTALE), and for few measures derived from the control essay: VocD (assessing productive lexical diversity), normed errors (assessing productive accuracy), words per minute (assessing productive written fluency), and holistic scores (assessing overall quality of production). We measured lexical learning (depth and breadth) via an adapted Vocabulary Knowledge Scale (VKS) and a free association test. Cognitive load was measured in the three essays (Control, Timed, Untimed) using normed number of errors and holistic scores (TOEFL criteria). The number of errors and essay scores were obtained from two raters (interrater reliability Pearson’s r=.78-91). Generalized linear mixed models showed no difference in the breadth and depth of keyword knowledge after writing Sentences, Timed essays, and Untimed essays. The task-based measurements found that Control and Timed essays had similar holistic scores, but that Untimed essay had better quality than Timed essay. Also, Untimed essay was the most accurate, and Timed essay the most error prone. Concluding, using keywords in Timed, but not Untimed, essays increased cognitive load, leading to more errors and lower quality. Still, writing sentences and essays yielded similar lexical learning, and differences in the cognitive load between Timed and Untimed essays did not affect lexical acquisition.

Keywords: learning academic words, writing essays, cognitive load, english as an L2

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Authors: Imen Blibech, Mohiedine Ksantini, Mohamed Bouaziz

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Prays oleae is a major insect of olive in the Mediterranean Region. In an effort to find effective and affordable ways of controlling this pest, larvicidal activity of essential oils from Tunisian Thymus capitatus were analyzed in comparison to Azadirachtin, a biologically active compound insecticide. The essential oils were extracted by hydrodistillation, and their chemical composition was determined by gas liquid-chromatography coupled with mass spectroscopy. The main components of chemical components were oxygenated monoterpenes (60.24%). The most abundant oxygenated monoterpenes were carvacrol (54.11%). Monoterpenes hydrocarbons were much more abundant and dominated by the o-cymene (16.68%). Both active compounds of Azadirachtin and Thymus capitatus oil extracts exhibited significant larvicidal activity against P. oleae with LC50 values 81.30 ppm and 52.49 ppm respectively. Dose-response relationships were established with almost 100% mortality when using the highest dose 100 ppm of T. capitatus oil extracts and 80 ppm of Azadirachtin. At the lowest dose (10 ppm), T. capitatus oil extracts and Azadirachtin caused 60% and 76% larval mortality in 48 hours respectively. The larval mortality rate greatly decreased with increases of the dilution of both oil extract compounds. Larval development duration appeared to be prolonged to about 12 days for larvae feeding on control diet. The maximum antifeedant activity was shown by both T. capitatus oil extract and Azadirachtin at LC90 values (47.5 and 50.1 ppm respectively). Tunisian T. capitatus oil extract used at low concentrations could be considered as eco-friendly promising insecticide similar to Azadirachtin that has significant potential for the biological control of P. oleae.

Keywords: Thymus capitatus, chemical composition, azadirachtin, larvicidal effects, antifeedant activity, Prays oleae

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Authors: Deawan Rakin Ahamed Remal, Sinthia Chowdhury, Sharun Akter Khushbu, Sheak Rashed Haider Noori

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Native Speech to text synthesis has its own leverage for the purpose of mankind. The extensive nature of art to speaking different accents is common but the purpose of communication between two different accent types of people is quite difficult. This problem will be motivated by the extraction of the wrong perception of language meaning. Thus, many existing automatic speech recognition has been placed to detect text. Overall study of this paper mentions a review of NSTTR (Native Speech Text to Text Recognition) synthesis compared with Text to Text recognition. Review has exposed many text to text recognition systems that are at a very early stage to comply with the system by native speech recognition. Many discussions started about the progression of chatbots, linguistic theory another is rule based approach. In the Recent years Deep learning is an overwhelming chapter for text to text learning to detect language nature. To the best of our knowledge, In the sub continent a huge number of people speak in Bangla language but they have different accents in different regions therefore study has been elaborate contradictory discussion achievement of existing works and findings of future needs in Bangla language acoustic accent.

Keywords: TTR, NSTTR, text to text recognition, deep learning, natural language processing

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Authors: Chiou-Shiue Ko, Pei-Fang Wu, Shu-hsien Tseng

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The researchers adopted two-year action research to investigate the professional collaborative process and development in learning communities for both early childhood and early childhood special education teachers on implementing the children’s school success curriculum framework. The participating teachers were recruited from three preschool sites for this current study. Research data were collected from multiple methods in order to ensure the data quality and validity. The results showed that participating educators had achieved professional growth, and they became more aware of teaching intentions and the preparation for the curriculum. Teachers in this research become more child-focused in teaching and create opportunities for children to participate in classroom activities and routines. The researcher also finds teachers’ participation levels were driven by each individual personality; during professional growth, some teachers are more proactive and reflective, and some are not. According to the research findings, suggestions for future studies and practices are provided.

Keywords: children’s school success curriculum framework, early childhood special education, preschool education, professional learning community

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Authors: F. Ruiz-Fuster

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Arnold’s redefinition of human motives can sustain a psychology of education which emphasizes the beauty of knowledge and the exercise of intellectual functions. Thus, education instead of focusing on skills and learning by doing would be centered on ‘the widest reaches of the human spirit’. One way to attain it is by developing children’s inherent interest. Arnold takes into account the fact that the desire to know is the inherent interest which leads students to explore and learn. She also emphasizes the need of exercising human functions as thinking, judging and reasoning. According to Arnold, the influence of psychological theories of motivation in education has derived in considering that all learning and school tasks should derive from children’s needs and impulses. The desire to know and the curiosity have not been considered as basic and active as any instinctive drive or basic need, so there has been an attempt to justify and understand how biological drives guide student’s learning. However, understanding motives and motivation not as a drive, an instinct or an impulse guided by our basic needs, but as a want that leads to action can help to understand, from a psychological perspective, how teachers can motivate students to learn, strengthening their desire and interest to reason and discover the whole new world of knowledge.

Keywords: academic motivation, interests, desire to know, educational psychology, intellectual functions

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Authors: Jacqueline Rose T. Alipo-on, Francesca Isabelle F. Escobar, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar Al Dahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases, which are considered one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis of ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heartbeat types. The dataset used in this work is the synthetic MIT-BIH Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: heartbeat classification, convolutional neural network, electrocardiogram signals, generative adversarial networks, long short-term memory, ResNet-50

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Authors: Taher S. Ababneh, Taghreed M. A. Jazzazi, Tareq M. A. Alshboul

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The inhibiting action against aluminum corrosion by three derivatives of 1,8-bis (benzylideneamino) naphthalene (BN) Schiff base has been investigated by means of DFT quantum chemical calculations at the B3LYP/6-31G(d) level of theory. The derivatives (CBN, NBN and MBN) were prepared from the condensation reaction of 1,8-diaminonaphthalene with substituted benzaldehyde (4-CN, 3-NO₂ and 3,4-(OMe)₂, respectively). Calculations were conducted to study the adsorption of each Schiff base on aluminum surface to evaluate its potential as a corrosion inhibitor. The computational structural features and electronic properties of each derivative such as relative energies and energies of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) have been reported. Thermodynamic functions and quantum chemical parameters such as the hardness of the inhibitor, the softness and the electrophilicity index were calculated to determine the derivative of the highest inhibition efficiency.

Keywords: corrosion, aluminum, DFT calculation, 1, 8-diaminonaphthalene, benzaldehyde

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Authors: Li Wang

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The explosive of technology advances has opened up many avenues of career options for engineering graduates. Hence, how relevant their learning at university is very much dependent on their actual jobs. Bridging the gap between education and industrial practice is important, but it also becomes evident how both engineering education and industrial training can be leveraged at the same time and balance between what students should grasp at university and what they can be continuously trained at the working environment. Through a case study of developing a commercial product, this paper presents the required level of depth of technical knowledge and skills for some typical engineering jobs (for mechanical/materials engineering). It highlights the necessary collaboration for industry, university, and accreditation bodies to work together to nurture the next generation of engineers.

Keywords: leverage, collaboration, career, industry, engineering education

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Authors: Jonathan A. Sánchez Muñoz, Gustavo Flores Eraña, Juan M. Silva

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Mexican Mezcal industry has reached attention during the last decade due to it has been a popular beverage demanded by North American and European markets, reaching popularity due to its crafty character. Despite its wide demand, productive processes are still made with rudimentary equipment, and there is a lack of evidence to improve kiln energy efficiency. Tec21 is a challenge-based learning curricular model implemented by Tecnológico de Monterrey since 2019, where each formation unit requires an industrial partner. “Problem processes solution” is a formation unity designed for mechatronics engineers, where students apply the acquired knowledge in thermofluids and apply electronic. During five weeks, students are immersed in an industrial problem to obtain a proper level of competencies according to formation unit designers. This work evaluates the competencies acquired by the student through qualitative research methodology. Several evaluation instruments (report, essay, and poster) were selected to evaluate etic argumentation, principles of sustainability, implemented actions, process modelling, and redesign feasibility.

Keywords: applied electronic, challenge based learning, competencies, mezcal industry, thermofluids

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Authors: Dorsaf Ben Malek

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The function of culture in language teaching changed because of globalization and the latest technologies. English became a lingua franca which resulted in altering the teaching objectives. The re-evaluation of cultural awareness is one of them. Business English teaching has also been subject to all these changes. It is therefore a wrong idea if we try to consider it as a diffusion of unlimited listing of lexis, diagrams, charts, and statistics. In fact, business students’ future career will require business terminology together with intercultural communicative competence (ICC) to handle different multicultural encounters and contribute to the international community. The first part of this paper is dedicated to the necessity of empowering business students with intercultural communicative competence and the second turns around the potential of multicultural literature in implementing ICC in business English teaching. This was proved through a qualitative action research done on a group of Tunisian MA business students. It was an opportunity to discover the potential of multicultural literature together with inquiry-based learning in enhancing business students’ intercultural communicative competence. Data were collected through classroom observations, journals and semi-structured interviews. Results were in favour of using multicultural literature to enhance business students’ ICC. In addition, the short story may be a motivating tool to read literature, and inquiry-based learning can be an effective approach to teaching literature.

Keywords: intercultural communicative competence, multicultural literature, short stories, inquiry-based learning

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Authors: Raed Kouta

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A fuel cell is a multi-physical system. Its electrical performance depends on chemical, electrochemical, fluid, and mechanical parameters. Many studies focus on physical and chemical aspects. Our study contributes to the evaluation of the influence of mechanical aspects on the performance of a fuel cell. This study is carried out as part of a reliability approach. Reliability modeling allows to consider the uncertainties of the incoming parameters and the probabilistic modeling of the outgoing parameters. The fuel cell studied is the one often used in land, sea, or air transport. This is the Low-Temperature Proton Exchange Membrane Fuel Cell (PEMFC). This battery can provide the required power level. One of the main scientific and technical challenges in mastering the design and production of a fuel cell is to know its behavior in its actual operating environment. The study proposes to highlight the influence on the production of electrical energy: Mechanical design and manufacturing parameters and their uncertainties (Young module, GDL porosity, permeability, etc.). The influence of the geometry of the bipolar plates is also considered. An experimental design is proposed with two types of materials as well as three geometric shapes for three joining pressures. Other experimental designs are also proposed for studying the influence of uncertainties of mechanical parameters on cell performance. - Mechanical (static, dynamic) and thermal (tightening - compression, vibrations (road rolling and tests on vibration-climatic bench, etc.) loads. This study is also carried out according to an experimental scheme on a fuel cell system for vibration loads recorded on a vehicle test track with three temperatures and three expected performance levels. The work will improve the coupling between mechanical, physical, and chemical phenomena.

Keywords: fuel cell, mechanic, reliability, uncertainties

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Authors: Ayanda P. Deliwe, Storm B. Watson

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The COVID-19 pandemic has disrupted the established practices of higher education institutions (HEIs). Most higher education institutions worldwide had to shift from traditional face-to-face to online learning. The online environment and new online tools are disrupting the way in which higher education is presented. Furthermore, the structures of higher education institutions have been impacted by rapid advancements in information and communication technologies. Emerging technologies should not be viewed in a negative light because, as opposed to the traditional curriculum that worked to create productive and efficient researchers, emerging technologies encourage creativity and innovation. Therefore, using technology together with traditional means will enhance teaching and learning. Emerging technologies in higher education not only change the experience of students, lecturers, and the content, but it is also influencing the attraction and retention of students. Higher education institutions are under immense pressure because not only are they competing locally and nationally, but emerging technologies also expand the competition internationally. Emerging technologies have eliminated border barriers, allowing students to study in the country of their choice regardless of where they are in the world. Higher education institutions are becoming indifferent as technology is finding its way into the lecture room day by day. Academics need to utilise technology at their disposal if they want to get through to their students. Academics are now competing for students' attention with social media platforms such as WhatsApp, Snapchat, Instagram, Facebook, TikTok, and others. This is posing a significant challenge to higher education institutions. It is, therefore, critical to pay attention to emerging technologies in order to see how they can be incorporated into the classroom in order to improve educational quality while remaining relevant in the work industry. This study aims to understand how emerging technologies have been utilised at Nelson Mandela University in presenting teaching and learning activities since April 2020. The primary objective of this study is to analyse how academics are incorporating emerging technologies in their teaching and learning activities. This primary objective was achieved by conducting a literature review on clarifying and conceptualising the emerging technologies being utilised by higher education institutions, reviewing and analysing the use of emerging technologies, and will further be investigated through an empirical analysis of the use of emerging technologies at Nelson Mandela University. Findings from the literature review revealed that emerging technology is impacting several key areas in higher education institutions, such as the attraction and retention of students, enhancement of teaching and learning, increase in global competition, elimination of border barriers, and highlighting the digital divide. The literature review further identified that learning management systems, open educational resources, learning analytics, and artificial intelligence are the most prevalent emerging technologies being used in higher education institutions. The identified emerging technologies will be further analysed through an empirical analysis to identify how they are being utilised at Nelson Mandela University.

Keywords: artificial intelligence, emerging technologies, learning analytics, learner management systems, open educational resources

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Authors: Wendi Dunham, Kimberly Floyd

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The constructivist approach to learning is a theoretical orientation that posits that individuals create their own understanding and knowledge of the world through their experiences and interactions. This approach emphasizes that learning is an active process and that individuals are not passive recipients when constructing their understanding of their world. When used concurrently with trauma-informed practices, a constructivist approach can inform the development of a framework for students and teachers that supports their social, emotional, and mental health in addition to enabling academic success. This framework can be applied to teachers and students. When applied to teachers, it can be used to achieve purposeful coping mechanisms through restorative justice and dispositional mindfulness. When applied to students, the framework can implement proactive, student-based practices such as Response to Intervention (RtI) and the 4 Rs to connect resiliency and intervention to academic learning. Using a constructivist, trauma-informed framework can provide students with a greater sense of control and agency over their trauma experiences and impart confidence in achieving school success.

Keywords: trauma, trauma informed practices in education, constructivist theory framework, school responses to trauma, trauma informed supports for teachers, trauma informed strategies for students, restorative justice, mindfulness, response to intervention, the 4 R's, resiliency

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Authors: Jan-Peter Mund, Christian Kind

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In view of the ongoing climate change and global warming, fires along railways in Germany are occurring more frequently, with sometimes massive consequences for railway operations and affected railroad infrastructure. In the absence of systematic studies within the infrastructure network of German Rail, little is known about the causes of such embankment fires. Since a further increase in these hazards is to be expected in the near future, there is a need for a sound knowledge of triggers and drivers for embankment fires as well as methodical knowledge of prediction tools. Two predictable future trends speak for the increasing relevance of the topic: through the intensification of the use of rail for passenger and freight transport (e.g..: doubling of annual passenger numbers by 2030, compared to 2019), there will be more rail traffic and also more maintenance and construction work on the railways. This research project approach uses satellite data to identify historical embankment fires along rail network infrastructure. The team links data from these fires with infrastructure and weather data and trains a machine-learning model with the aim of predicting fire hazards on sections of the track. Companies reflect on the results and use them on a pilot basis in precautionary measures.

Keywords: embankment fires, railway maintenance, machine learning, remote sensing, VIIRS data

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Authors: Rifda Naufalin, Nurul Latifasari, Siti Nuryanti, Muna Ridha Hanifah

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Kecombrang is a Zingiberaceae plant which has antioxidant properties. The high antioxidant content in kecombrang flowers has the potential to be processed as a functional beverage raw material so that it can be used as an ingredient in making herbal teas. The purpose of this study was to determine the chemical components, physicochemistry, antioxidant activity and sensory characteristics of kecombrang tea. The research methodology was carried out by using a completely randomized design with processing factors of kecombrang tea namely blanching and non-blanching, fermentation and non-fermentation, and the optimal time for drying kecombrang tea. The best treatment combination based on the effective index method is the treatment of the blanching process followed by drying at a temperature of 50ᵒC until the 2% moisture content can produce kecombrang tea with a total phenol content of 5.95 mg Tannic Acid Equivalent (TAE) / gram db, total flavonoid 3%, pH 4.5, and antioxidant activity 82.95%, red color, distinctive aroma of tea, fresh taste, and preferred by panelists.

Keywords: kecombrang tea, blanching, fermentation, total phenol, and antioxidant activity

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Authors: Benhamza Moussa, Aissaoui Marwa, Touati Mounira, Chaoui Widad

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The Guelma-Bouchegouf irrigated area is located in the northeast of Algeria, and it extends about 80 km. It was commissioned in 1996, with an irrigable area of 9250 ha, it spreads on both banks of the Seybouse Wadi and it is subdivided into five autonomous distribution sectors. In order to assess the state of groundwater quality, the results of the chemical analyzes were plotted on the Piper diagram, which shows that the chemical facies are sulfate-calcium chloride and sulfate-calcium with a slight tendency to migrate to chlorinated sulphate - sodium. The predominance of sulphates in the waters of the region is geologically explained by the existence in the Guelma Basin of evaporitic deposits, which are mainly represented by rock salt and gypsum. In addition to this natural origin, we can mention the anthropogenic origin, following the use of chemical fertilizers in the Guelma-Bouchegouf irrigated area. Na⁺ and Mg²⁺ show moderate to significant mineralization of water, closely correlated with very high conductivities. The values of the recorded conductivities vary from 1360 μs / cm (P3) to 4610 μs / cm (P10). These important values are due to dissolved salts on the one hand and the leaching of fertilizers by irrigation water on the other hand. NO₃⁻ and NH₄⁺ show little to significant pollution throughout the study area. Phosphate represents significant pollution, with excessive values far exceeding the allowable standard. With respect to ammonium, 87% of the sampling points present little pollution and 13 % significant pollution. Regarding phosphates, in the form of PO₄³⁻, groundwater in the study area represents significant pollution; all values far exceed the allowable standard.

Keywords: groundwater, organic parameters, standards, Pollution

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Authors: Tajinder Pal Singh

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Teaching of mathematics to engineering students is an open ended problem in education. The main goal of mathematics learning for engineering students is the ability of applying a wide range of mathematical techniques and skills in their engineering classes and later in their professional work. Most of the undergraduate engineering students and faculties feels that no efforts and attempts are made to demonstrate the applicability of various topics of mathematics that are taught thus making mathematics unavoidable for some engineering faculty and their students. The lack of understanding of concepts in engineering mathematics may hinder the understanding of other concepts or even subjects. However, for most undergraduate engineering students, mathematics is one of the most difficult courses in their field of study. Most of the engineering students never understood mathematics or they never liked it because it was too abstract for them and they could never relate to it. A right balance of application and concept based teaching can only fulfill the objectives of teaching mathematics to engineering students. It will surely improve and enhance their problem solving and creative thinking skills. In this paper, some practical (informal) ways of making mathematics-teaching application based for the engineering students is discussed. An attempt is made to understand the present state of teaching mathematics in engineering colleges. The weaknesses and strengths of the current teaching approach are elaborated. Some of the causes of unpopularity of mathematics subject are analyzed and a few pragmatic suggestions have been made. Faculty in mathematics courses should spend more time discussing the applications as well as the conceptual underpinnings rather than focus solely on strategies and techniques to solve problems. They should also introduce more ‘word’ problems as these problems are commonly encountered in engineering courses. Overspecialization in engineering education should not occur at the expense of (or by diluting) mathematics and basic sciences. The role of engineering education is to provide the fundamental (basic) knowledge and to teach the students simple methodology of self-learning and self-development. All these issues would be better addressed if mathematics and engineering faculty join hands together to plan and design the learning experiences for the students who take their classes. When faculties stop competing against each other and start competing against the situation, they will perform better. Without creating any administrative hassles these suggestions can be used by any young inexperienced faculty of mathematics to inspire engineering students to learn engineering mathematics effectively.

Keywords: application based learning, conceptual learning, engineering mathematics, word problem

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Authors: Svetlana Guryeva, Inna Kornienko, Andrey Usanov, Dmitry Usanov, Elena Petersen

Abstract:

Every day cells in our organism are exposed to various factors: chemical agents, reactive oxygen species, ionizing radiation, and others. These factors can cause damage to DNA, cellular membrane, intracellular compartments, and proteins. The fate of cells depends on the exposure intensity and duration. The prolonged and intense exposure causes the irreversible damage accumulation, which triggers the permanent cell cycle arrest (cellular senescence) or cell death programs. In the case of low dose of impacts, it can lead to cell renovation and to cell functional state improvement. Therefore, it is a pivotal question to investigate the factors and doses that result in described positive effects. In order to estimate the influence of different agents, the proliferation index and levels of cell death markers (annexin V/propidium iodide), senescence-associated β-galactosidase, and lipofuscin were measured. The experiments were conducted on primary human fibroblasts of the 8th passage. According to the levels of mentioned markers, these cells were defined as senescent cells. The effect of low-frequency magnetic field was investigated. Different modes of magnetic field exposure were tested. The physical agents were compared with chemical agents: metformin (10 mM) and taurine (0.8 mM and 1.6 mM). Cells were incubating with chemicals for 5 days. The highest decrease in the level of senescence-associated β-galactosidase (21%) and lipofuscin (17%) was observed in the primary senescent fibroblasts after 5 days after double treatments with 48 h intervals with low-frequency magnetic field. There were no significant changes in the proliferation index after magnetic field application. The cytotoxic effect of magnetic field was not observed. The chemical agent taurine (1.6 mM) decreased the level of senescence-associated β-galactosidase (23%) and lipofuscin (22%). Metformin improved the activity of senescence-associated β-galactosidase on 15% and the level of lipofuscin on 19% in this experiment. According to these results, the effect of double treatment with 48 h interval with low-frequency magnetic field and the effect of taurine (1.6 mM) were comparable to the effect of metformin, for which anti-aging properties are proved. In conclusion, this study can become the first step towards creation of the standardized system for the investigation of different effects on senescent cells.

Keywords: biomarkers, magnetic field, metformin, primary fibroblasts, senescence, taurine

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Authors: S. Potgieter-Vermaak, N. Bain, A. Brown, K. Shaw

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It is well-known from public news media that air pollution is a health hazard and is responsible for early deaths. The quantification of the relationship between air quality and health is a probing question not easily answered. It is known that airborne particulate matter (APM) <2.5µm deposits in the tracheal and alveoli zones and our research probes the possibility of quantifying pulmonary injury by linking reactive oxygen species (ROS) in these particles to DNA damage. Currently, APM mass concentration is linked to early deaths and limited studies probe the influence of other properties on human health. To predict the full extent and type of impact, particles need to be characterised for chemical composition and structure. APMs are routinely analysed for their bulk composition, but of late analysis on a micro level probing single particle character, using micro-analytical techniques, are considered. The latter, single particle analysis (SPA), permits one to obtain detailed information on chemical character from nano- to micron-sized particles. This paper aims to provide a snapshot of studies using data obtained from chemical characterisation and its link with in-vitro studies to inform on personal health risks. For this purpose, two studies will be compared, namely, the bioaccessibility of the inhalable fraction of urban road dust versus total suspended solids (TSP) collected in the same urban environment. The significant influence of metals such as Cu and Fe in TSP on DNA damage is illustrated. The speciation of Hg (determined by SPA) in different urban environments proved to dictate its bioaccessibility in artificial lung fluids rather than its concentration.

Keywords: air pollution, human health, in-vitro studies, particulate matter

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Traditional optimization methods like evolutionary algorithms are widely used in production processes to find an optimal or near-optimal solution of control parameters based on the simulated environment space of a process. These algorithms are computationally intensive and therefore do not provide the opportunity for real-time optimization. This paper utilizes the Deep Reinforcement Learning (DRL) framework to find an optimal or near-optimal solution for control parameters. A model based on maximum a posteriori policy optimization (Hybrid-MPO) that can handle both numerical and categorical parameters is used as a benchmark for comparison. A comparative study shows that DRL can find optimal solutions of similar quality as compared to evolutionary algorithms while requiring significantly less time making them preferable for real-time optimization. The results are confirmed in a large-scale validation study on datasets from production and other fields. A trained XGBoost model is used as a surrogate for process simulation. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, evolutionary algorithms, production process optimization, real-time optimization, hybrid-MPO

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Authors: Jiaxin Shi, Kaifeng Hao, Qingfan An, Zeng Peng

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Due to a lack of data sources and data processing techniques, it has always been difficult to quantify public space quality, which includes urban construction quality and how it is perceived by people, especially in large urban areas. This study proposes a quantitative research method based on the consideration of emotional health and physical health of the built environment. It highlights the low quality of public areas in Tianjin, China, where there are many negative elements. Deep learning technology is then used to measure how effectively people perceive urban areas. First, this work suggests a deep learning model that might simulate how people can perceive the quality of urban construction. Second, we perform semantic segmentation on street images to identify visual elements influencing scene perception. Finally, this study correlated the scene perception score with the proportion of visual elements to determine the surrounding environmental elements that influence scene perception. Using a small-scale labeled Tianjin street view data set based on transfer learning, this study trains five negative spatial discriminant models in order to explore the negative space distribution and quality improvement of urban streets. Then it uses all Tianjin street-level imagery to make predictions and calculate the proportion of negative space. Visualizing the spatial distribution of negative space along the Tianjin Inner Ring Road reveals that the negative elements are mainly found close to the five key districts. The map of Tianjin was combined with the experimental data to perform the visual analysis. Based on the emotional assessment, the distribution of negative materials, and the direction of street guidelines, we suggest guidance content and design strategy points of the negative phenomena in Tianjin street space in the two dimensions of perception and substance. This work demonstrates the utilization of deep learning techniques to understand how people appreciate high-quality urban construction, and it complements both theory and practice in urban planning. It illustrates the connection between human perception and the actual physical public space environment, allowing researchers to make urban interventions.

Keywords: human perception, public space quality, deep learning, negative elements, street images

Procedia PDF Downloads 115

Authors: Srinivasa Rao Idapalapati, Manssour Habbash

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As mobile connectedness continues to sweep across the landscape, the value of deploying mobile technology to the service of learning and teaching appears to be both self-evident and unavoidable. To this end, this study explores the reasons for the reluctance of teachers in Saudi Arabia to use mobiles in EFL (English as a Foreign Language) classes for teaching and learning purposes. The main objective of this study is a qualitative analysis of the responses of the views of the teachers at a university in Saudi Arabia about the use of mobile phones in classrooms for educational purposes. Driven by the hypothesis that the teachers in Saudi Arabian universities aren’t prepared well enough to use mobile phones in classrooms for educational purposes, this study examines the data obtained through a questionnaire provided to about hundred teachers working at a university in Saudi Arabia through convenient sampling method. The responses are analyzed by qualitative interpretive method and found that teachers and the students are in confusion whether to use mobiles, and need some training sessions on the use of mobile phones in classrooms for educational purposes. The outcome of the analysis is discussed in light of the concerns bases adoption model and the inferences are provided in a descriptive mode.

Keywords: mobile assisted language learning, technology adoption, classroom instruction, concerns based adoption model

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Authors: Kalsoom Shaikh, Ghulam Sarwar Gachal, Saima Memon

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Our study aimed to assess diversity and habitats of amphibian fauna in Sindh province as amphibians are among most vulnerable animals and the risk of their extinction is increasing in many parts of world mainly due to habitat degradation. Present study consisted of field surveys and laboratory analytical work; field surveys were carried out to confirm amphibian diversity and collection of water samples from their habitats, whereas laboratory work was conducted for identification of species and analysis of water quality of habitats through physico-chemical parameters. For identification of amphibian species, morphology was thoroughly examined using taxonomic key, whereas water quality was assessed via physico-chemical parameters including pH, electric conductivity (EC), total dissolved solids (TDS), total hardness (T. Hard), total alkalinity (T. Alk), chloride (Cl), carbon dioxide (CO₂), sulfate (SO₄), phosphate (PO₄), nitrite (NO₂) and nitrate (NO₃) using material and methods of analytical grade. pH value was analyzed using pH meter, whereas levels of EC and TDS were recorded using conductivity meter and TDS meter, respectively. Other parameters with exception of non-metallic parameters (SO₄, PO₄, NO₂, and NO₃) were analyzed through distinct titration methods. Concentration of non-metallic parameters was evaluated using ultra-violet spectrophotometer. This study revealed existence of four amphibian species including Hoplobatrachus tigerinus, Euphlyctis cyanophlyctis, Allopa hazarensis belonging to Family Ranidae and Bufo stomaticus (Family Bufonidae) randomly distributed in district Ghotki, Jamshoro, Kashmor, Larkana, Matiari and Shikarpur in Sindh. Assessment of aquatic habitats in different areas found value of parameters as followed: Habitats in district Ghoki (pH: 7.8 ± 0.3, EC: 2165.3 ± 712.6, TDS: 1507.0 ± 413.1, T-Hard: 416.4 ± 67.5, T. Alk: 393.4 ± 78.4, Cl: 362.4 ± 70.1, CO₂: 21.1 ± 3.5, SO₄: 429.3 ± 100.1, PO₄: 487.5 ± 122.5, NO₂: 13.7 ± 1.0, NO₃: 14.7 ± 2.5), district Jamshoro habitats (pH: 8.1 ± 0.4, EC: 2403.8 ± 55.4, TDS: 1697.2 ± 77.0, T. Hard: 548.7 ± 43.2, T. Alk: 294.4 ± 29.0, Cl: 454.7 ± 50.8 CO₂: 16.9 ± 2.4, SO₄: 713.0 ± 49.3, PO₄: 826.2 ± 53.0, NO₂: 15.2 ± 3.4, NO₃: 21.6 ± 3.7), habitats in Kashmor district (pH: 8.0 ± 0.5, EC: 2450.3 ± 610.9, TDS: 1745.3 ± 440.9, T. Hard: 624.6 ± 305.8, T. Alk: 445.7 ± 120.5, Cl: 448.9 ± 128.8, CO₂: 18.9 ± 4.5, SO₄: 619.8 ± 205.8, PO₄: 474.1 ± 94.2, NO₂: 15.2 ± 3.1, NO₃ 14.3 ± 2.6), district Larkana habitats (pH: 8.4 ± 0.4, EC: 2555.8 ± 70.3, TDS: 1784.4 ± 36.9, T. Hard: 623.0 ± 42.5, T. Alk: 329.6 ± 36.7, Cl: 614.3 ± 89.5, CO₂: 17.6 ± 1.2, SO₄: 845.1 ± 67.6, PO₄: 895.0 ± 61.4, NO₂: 13.6 ± 3.8, NO₃: 23.1 ± 2.8), district Matiari habitats (pH: 8.0 ± 0.4 EC: 2492.3 ± 928.1, TDS: 430.0 ± 161.3, T. Hard: 396.7 ± 183.3, T. Alk: 388.1 ± 97.4, Cl: 551.6 ± 73.4, CO₂: 15.8 ± 2.9, SO₄: 576.5 ± 200.0, PO₄: 434.7 ± 100.6, NO₂: 15.8 ± 2.9, NO₃: 15.2 ± 3.0) and habitats in Shikarpur district (pH: 8.1 ± 0.6, EC: 2191.7 ± 765.1, TDS: 1764.9 ± 409.2, T. Hard: 431.9 ± 68.4,T. Alk: 350.3 ± 44.3, Cl: 381.5 ± 29.5, CO₂: 18.0 ± 4.0, SO₄: 518.8 ± 97.9, PO₄: 493.6 ± 64.6, NO₂: 14.0 ± 0.8, NO₃: 16.1 ± 2.8). Values of physico-chemical parameters were found higher than permissible level of Environmental Protectiona Agency (EPA). Monthly variation in concentration of physico-chemical parameters was also prominently recorded at all the study locals. This study discovered poor diversity of amphibian fauna and condition of their habitats was also observed as pitiable. This study established base line information that may be used in execution of an effective management plan and future monitoring of amphibian diversity and their habitats in Sindh.

Keywords: amphibians, diversity, habitats, Pakistan, Sindh

Procedia PDF Downloads 164

Authors: Mark Anthony Burdeos, Kara Ella Catoto, Alraine Pauyon, Elesar Malicoban

Abstract:

This study sought to develop, validate, and implement the WebQuest and Online Treasure Hunt as instructional materials in teaching Motion in One Dimension for Grade 7 students and to determine its effects on the students’ conceptual learning, performance and attitude towards Physics. In the development stage, several steps were taken, such as the actual planning and developing the WebQuest and Online Treasure Hunt and making the lesson plan and achievement test. The content and the ICT(Information Communications Technology) effect of the developed instructional materials were evaluated by the Content and ICT experts using adapted evaluation forms. During the implementation, pretest and posttest were administered to determine students’ performance, and pre-attitude and post-attitude tests to investigate students’ attitudes towards Physics before and after the WebQuest and Online Treasure Hunt activity. The developed WebQuest and Online Treasure Hunt passed the validation of Content experts and ICT experts. Students acquired more knowledge on Motion in One Dimension and gained a positive attitude towards Physics after the utilization of WebQuest and Online Treasure Hunt, evidenced significantly higher scores in posttest compared to pretest and higher ratings in post-attitude than pre-attitude. The developed WebQuest and Online Treasure Hunt were proven good in quality and effective materials in teaching Motion in One Dimension and developing a positive attitude towards Physics. However, students performed better in the pretest and posttest and rated higher in the pre-attitude and post-attitude tests in the WebQuest than in the Online Treasure Hunt. This study would provide significant learning experiences to the students that would be useful in building their knowledge, in understanding concepts in a most understandable way, in exercising to use their higher-order thinking skills, and in utilizing their capabilities and abilities to relate Physics topics to real-life situations thereby, students can have in-depth learning about Motion in One Dimension. This study would help teachers to enhance the teaching strategies as the two instructional materials provide interesting, engaging, and innovative teaching-learning experiences for the learners, which are helpful in increasing the level of their motivation and participation in learning Physics. In addition, it would provide information as a reference in using technology in the classroom and to determine which of the two instructional materials, WebQuest and Online Treasure Hunt, is suitable for the teaching-learning process in Motion in One Dimension.

Keywords: ICT integration, motion in one dimension, online treasure hunt, Webquest

Procedia PDF Downloads 176