Search results for: learning and teaching methods

Authors: Van Thien NGO

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The purpose of the study is to examine the effect of student response systems in computer-based formative assessment on learning outcomes. The backward design course is a tool to be applied for collecting necessary assessment evidence. The quasi-experimental research design involves collecting pre and posttest data on students assigned to the control group and the experimental group. The sample group consists of 150 college students randomly selected from two of the eight classes of electrical and electronics students at Cao Thang Technical College in Ho Chi Minh City, Vietnam. Findings from this research revealed that the experimental group, in which student response systems were applied, got better results than the controlled group, who did not apply them. Results show that using student response systems for technology-based formative assessment is vital and meaningful not only for teachers but also for students in the teaching and learning process.

Keywords: student response system, computer-based formative assessment, learning outcome, backward design course

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Authors: Ugahara Bin Mahyuddin Yunus

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In English Language Teaching, it cannot be denied that the backgrounds of English teachers do affect the way they teach English to their students, which in turn will affect their students’ English learning itself. Thus, it is very important to understand who the English teachers are so that how they teach English to their students can be understood. One of their backgrounds that is essential to be highlighted is their culture. Certainly, they wittingly or not will bring the perspectives and values of their culture into their daily teaching practices. In other words, their cultural identities do shape how they teach their students. Cultural identities themselves actually consist of some elements, one of which is regional identity. Indeed, the culture of the region in which English teachers identify with has impact on their beliefs and actions during teaching. For this reason, this study aims to understand how the regional identity of English teachers influence the way they teach English to their students. This study is a qualitative study conducted in a multilingual and multicultural setting, namely Aceh, Indonesia. Here, four Acehnese English teachers were involved as the research participants. In addition, this study adopted poststructuralist perspective to identity as the theoretical framework. Three research instruments were used in this study, namely semi-structured interviews, classroom observation, and teacher journal. The data gained from these instruments were then analyzed by using thematic analysis. Obviously, the research about the regional identity of English teachers in English Language Teaching has been studied worldwide. However, little is still known about it in Indonesian context, let alone Indonesia itself is a super diverse country with 34 regions. As a result, this study presents a good opportunity to advance the knowledge of how the regional identity construction of English teachers in this setting is. The findings of the study revealed that their regional identity construction in teaching was highly influenced by their indigenous language and religious faith. Even, how they teach English in classroom, in fact, is related to these two things. The conclusion that can be drawn from this study is for these English teachers, in fact, their regional identity itself constitutes their use of local language and religious identity, which are considered by them as their core identity.

Keywords: English language teaching, English teachers, identity construction, regional identity

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Authors: Marie Pavelková, Hana Lukášová

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Pupils´ inquisitiveness at the beginning of their school attendance is reflected by characteristics of the questions they ask. Clearly most of the classroom communication sequences are initiated by the teacher. But the teaching process also includes questions initiated by pupils in the need to satisfy their need for knowledge. The purpose of our research is to present the results of our pre-research strategy of occurrence of pupil-initiated questions in math lessons at the lower elementary school level, and to reveal the extent to which they are influenced by the teacher´s teaching strategy. We used the research methods of direct and indirect observations of fifth year classes in primary school. We focused on questions asked by the pupils in their math lessons. Our research sample for the pre-research observation method was a collection of video recordings available online. We used them for analysing the nature of pupils´ questions identified there. On the basis of the analysis, we hereby present the results concerning the nature of pupils´ questions asked in math lessons on the lower elementary school level. The interpretation of the collected results will be the starting point for the selection of research strategies in the next research stages concerning pupils’ questions in the future.

Keywords: beginning of schooling, pre-research, questions of pupils, teaching strategy

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Authors: Olumide Yusuf Jimoh

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Reading comprehension is an interactive and purposeful process of getting meaning from and bringing meaning to a text. Over the years, teachers of the English Language (in Nigeria) have been glued to the monotonous method of making students read comprehension passages silently and then answer the questions that follow such passages without making the reading session interactive. Hence, students often find such exercises monotonous and boring. Consequently, students'’ interest in language learning continues to dwindle, and this often affects their overall academic performance. Relying on Communicative Accommodation Theory therefore, the study employed the qualitative research design method to x-ray Communicative Language Teaching Approach (CLTA) in reading comprehension. Moreover, techniques such as the Genuinely Collaborative Reading Approach (GCRA), Jigsaw reading, Pre-reading, and Post-reading tasks were examined. The researcher submitted that effective reading comprehension could not be done passively. Students must respond to what they read; they must interact not only with the materials being read but also with one another and with the teacher; this can be achieved by developing communicative and interactive reading programs.

Keywords: collaborative reading approach, communicative teaching, interactive reading program, pre-reading task, reading comprehension

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Authors: Fiseha M. Guangul, Annissa Muhammed, Aja O. Chikere

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Group task is one method to create the conducive environment for the active teaching-learning process. Performing group task with active involvement of students will benefit the students in many ways. However, in most cases all students do not participate actively in the group task, and hence the intended benefits are not acquired. This paper presents the improvements of students’ participation in the group task and learning from the group task by introducing different techniques to enhance students’ participation. For the purpose of this research Carpentry and Joinery II (WT-392) course from Wood Technology Department at Adama Science and Technology University was selected, and five groups were formed. Ten group tasks were prepared and the first five group tasks were distributed to the five groups in the first day without introducing the techniques that are used to enhance participation of students in the group task. On another day, the other five group tasks were distributed to the same groups and various techniques were introduced to enhance students’ participation in the group task. The improvements of students’ learning from the group task after the implementation of the techniques. After implementing the techniques the evaluation showed that significant improvements were obtained in the students’ participation and learning from the group task.

Keywords: group task, students participation, active learning, the evaluation method

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Authors: Nasser Al-Rawahi

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The study aims at determining self-regulated learning strategies used by Omani physical education candidates to learn sport skills. The data were collected by a self-regulated learning theory questionnaire. The sample of the study comprised of 145 undergraduate physical education students enrolled in the department of physical education at the College of Education, Sultan Qaboos University. The findings of the study revealed that the most commonly used strategies for learning sport skills by Omani physical education candidate are ‘the effort learning strategies, planning learning strategies and evaluation learning strategies’. However, the reflection learning strategies, self-monitoring and self-efficacy learning strategies were revealed as the least used strategies by the PE candidates in learning and acquiring sport skills. Based on these findings, suggestions and recommendations for future research were provided.

Keywords: learning strategies, physical education candidates, self-regulated learning theory, Oman

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Authors: Sara Fine-Meltzer

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An obvious, but ill-addressed hindrance to reading comprehension in academic English is poor vocabulary. Unfortunately, dealing with the problem is usually delayed until university entrance. It is the contention of this paper that the chore should be confronted much earlier and by using a very old-fashioned method. This presentation is accompanied by vocabulary lists for advanced level university students with explanations concerning the content and justification for the 500-word lists: how they change over time in accordance with evolving styles of academic writing. There are also sample quizzes and methods to ensure that the words are “absorbed” over time. There is a discussion of other vocabulary acquisition methods and conclusions drawn from the drawbacks of such methods. The paper concludes with the rationale for beginning the study of “academic” vocabulary earlier than is generally acceptable.

Keywords: academic vocabulary, old-fashioned methods, quizzes, vocabulary lists

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Authors: Oluwatofunmi Otobo

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This paper presents a review of the challenges of e-learning and e-learning technologies in tertiary institutions. This review is based on the researchers observations of the challenges of making use of ICT for learning in Nigeria using Adeyemi College of Education as a case study; this is in comparison to tertiary institutions in the UK, US and other more developed countries. In Nigeria and probably Africa as a whole, power is the major challenge. Its inconsistency and fluctuations pose the greatest challenge to making use of online education inside and outside the classroom. Internet and its supporting infrastructures in many places in Nigeria are slow and unreliable. This, in turn, could frustrate any attempt at making use of online education and e-learning technologies. Lack of basic knowledge of computer, its technologies and facilities could also prove to be a challenge as many young people up until now are yet to be computer literate. Personal interest on both the parts of lecturers and students is also a challenge. Many people are not interested in learning how to make use of technologies. This makes them resistant to changing from the ancient methods of doing things. These and others were reviewed by this paper, suggestions, and recommendations were proffered.

Keywords: education, e-learning, Nigeria, tertiary institutions

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Sotiria Tzivinikou, Dimitra Kagkara

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Teacher’s sense of self-efficacy can affect significantly both teacher’s and student’s performance. More specific, self-efficacy is associated with the learning outcomes as well as student’s motivation and self-efficacy. For example, teachers with high sense of self-efficacy are more open to innovations and invest more effort in teaching. In addition to this, effective inclusive education is associated with higher levels of teacher’s self-efficacy. Pre-service teachers with high levels of self-efficacy could handle student’s behavior better and more effectively assist students with special educational needs. Teacher preparation programs are also important, because teacher’s efficacy beliefs are shaped early in learning, as a result the quality of teacher’s education programs can affect the sense of self-efficacy of pre-service teachers. Usually, a number of pre-service teachers do not consider themselves well prepared to work with students with special educational needs and do not have the appropriate sense of self-efficacy. This study aims to investigate the factors that contribute to the improvement of the sense of self-efficacy of pre-service special educators by using an academic practicum training program. The sample of this study is 159 pre-service special educators, who also participated in the academic practicum training program. For the purpose of this study were used quantitative methods for data collection and analysis. Teacher’s self-efficacy was assessed by the teachers themselves with the completion of a questionnaire which was based on the scale of Teacher’s Sense of Efficacy Scale. Pre and post measurements of teacher’s self-efficacy were taken. The results of the survey are consistent with those of the international literature. The results indicate that a significant number of pre-service special educators do not hold the appropriate sense of self-efficacy regarding teaching students with special educational needs. Moreover, a quality academic training program constitutes a crucial factor for the improvement of the sense of self-efficacy of pre-service special educators, as additional for the provision of high quality inclusive education.

Keywords: inclusive education, pre-service, self-efficacy, training program

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Authors: Tlou J. Ramabu

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Programming is one of the challenging subjects in the field of computing. In the higher education sphere, some programming novices’ performance, retention rate, and success rate are not improving. Most of the time, the problem is caused by the slow pace of learning, difficulty in grasping the syntax of the programming language and poor logical skills. More importantly, programming forms part of major subjects within the field of computing. As a result, specialized pedagogical methods and innovation are highly recommended. Little research has been done on the potential productivity of the WhatsApp platform as part of a blended learning model. In this article, the authors discuss the WhatsApp group as a part of blended learning model incorporated for a group of programming novices. We discuss possible administrative activities for productive utilisation of the WhatsApp group on the blended learning overview. The aim is to take advantage of the popularity of WhatsApp and the time students spend on it for their educational purpose. We believe that blended learning featuring a WhatsApp group may ease novices’ cognitive load and strengthen their foundational programming knowledge and skills. This is a work in progress as the proposed blended learning model with WhatsApp incorporated is yet to be implemented.

Keywords: blended learning, higher education, WhatsApp, programming, novices, lecturers

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. That is why the need for automation of this task is urgent. A lot of studies have investigated the subject using different standard image processing descriptors and sometimes hand-crafted ones.In this work, we make a comparative study between classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN, Autoencoders, Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches

Keywords: pollens identification, features extraction, pollens classification, automated palynology

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Authors: Jian Wang

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Teachers’ lesson-based discussions presume central to their effective learning to teach. Whether and to what extent such discussions offer opportunities for teachers to learn to teach effectively is worth a careful empirical examination. This study examines this assumption by drawing on lesson-based discussions and relevant curriculum materials from Chinese teachers in three urban schools. Their lesson-based discussions consistently focused on pedagogical content knowledge and offered specific and reasoned suggestions for teachers to refine their teaching practices. The mandated curriculum and their working language-mediated their lesson-based discussions.

Keywords: Chinese teachers, curriculum materials, lesson discussion, mathematics instruction

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Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning

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Authors: T. T. K. Nguyen, T. H. Doan

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The study investigates students’ perceptions and students’ use of vocabulary learning strategies (VLS) among non-English majors at Ho Chi Minh City University of Technology (HUTECH). Three main issues addressed are (1) to determine students’ perception in terms of their awareness and the level of the importance of vocabulary learning strategies; (2) students’ use in terms of frequency and preference; (3) the correlation between students’ perception in terms of the level of the importance of vocabulary learning strategies and their use in terms of frequency. The mixed method is applied in this investigation; additionally, questionnaires focus on social groups, memory groups, cognitive groups, and metacognitive groups with 350 sophomores from four different majors, and 10 sophomores are invited to structured interviews. The results showed that the vocabulary learning strategies of the current study were well aware. All those strategies were perceived as important in learning vocabulary, and four groups of vocabulary were used frequently. Students’ responses in terms of preference also confirmed students’ use in terms of frequency. On the other hand, students’ perception correlated with students’ use in only the cognitive group of vocabulary learning strategies, but not the three others.

Keywords: vocabulary learning strategies, students' perceptions, students' use, mixed methods, non-English majors

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Authors: Ambika Perisamy, Asyriawati binte Mohd Hamzah

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The focus of this presentation is to discuss teacher professional development (TPD) through the use of technology. TPD is necessary to prepare teachers for future challenges they will face throughout their careers and to develop new skills and good teaching practices. We will also be discussing current issues in embracing technology in the field of early childhood education and the impact on the professional development of teachers. Participants will also learn to apply teaching and learning practices through the use of technology. One major objective of this presentation is to coherently fuse practical, technology and theoretical content. The process begins by concretizing a set of preconceived ideas which need to be joined with theoretical justifications found in the literature. Technology can make observations fairer and more reliable, easier to implement, and more preferable to teachers and principals. Technology will also help principals to improve classroom observations of teachers and ultimately improve teachers’ continuous professional development. Video technology allows the early childhood teachers to record and keep the recorded video for reflection at any time. This will also provide opportunities for her to share with her principals for professional dialogues and continuous professional development plans. A total of 10 early childhood teachers and 4 principals were involved in these efforts which identified and analyze the gaps in the quality of classroom observations and its co relation to developing teachers as reflective practitioners. The methodology used involves active exploration with video technology recordings, conversations, interviews and authentic teacher child interactions which forms the key thrust in improving teaching and learning practice. A qualitative analysis of photographs, videos, transcripts which illustrates teacher’s reflections and classroom observation checklists before and after the use of video technology were adopted. Arguably, although PD support can be magnanimously strong, if teachers could not connect or create meaning out of the opportunities made available to them, they may remain passive or uninvolved. Therefore, teachers must see the value of applying new ideas such as technology and approaches to practice while creating personal meaning out of professional development. These video recordings are transferable, can be shared and edited through social media, emails and common storage between teachers and principals. To conclude the importance of reflective practice among early childhood teachers and addressing the concerns raised before and after the use of video technology, teachers and principals shared the feasibility, practical and relevance use of video technology.

Keywords: early childhood education, reflective, improve teaching and learning, technology

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Authors: Petr Sulc, Hana Maresova

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This contribution focuses on online educational tools and language teaching, specifically on literary education in a multi-user virtual environment. The goal of this contribution is to give a basic overview of online language education and teaching in a virtual environment. The main goal of the research survey is to compare language (literary) education in a virtual environment with the traditional way of teaching in a typical classroom. The research concept will be mixed: a didactic test, the grounded theory method, and semi-structured questioning will be used. Kitely’s multi-user virtual environment and printed worksheets will be used for the comparison.

Keywords: online educational tools, virtual environment, virtual teaching objects, literary education, didactic test

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Authors: Gizem Eser Erdek

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This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

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Authors: Jeffrey Siphiwe Mkhize

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Twelve years of schooling for most South African children, particularly those children from disadvantaged past, are confronted with numerous and diverse challenges. These challenges range from infrastructural limitations, language of teaching, poor resources and varying family backgrounds. Likewise, schools are categorized to signify schools’ geographic location, poverty lines, societal class and type of students that the school are likely to enroll. Such categorization perpetuates particular lines of identities that are indirectly reinforced by the same system that seeks to redress. South African universities prefer point systems to determine students’ suitability to gain access to their programmes. Once students are admitted based on the qualifying points there is an assumed equity in the manner in which they receive tuition. They are assumed as equal; noting the widened access to South African universities as means to redress past inequalities. Given the challenges, inequalities, it is necessary to view higher education as a site for knowledge construction that is accessible to all students. Epistemological access is key to all students irrespective of their socio-economic status. This paper seeks to contribute to the discourse of student engagement using lecturer-student relationship as a lens to understand this phenomenon. Data were generated using South African Survey of Student Engagement, focus group interviews, semi-structured one-on-one-interviews as well as document analysis. The focus was on students registered for the first year of a Bachelor of Education degree as well as lecturers that teach high risk modules in this qualification at the same level. The findings suggest that lecturers are challenged by overcrowded classrooms and over-enrolled modules; this challenge hampers their good intentions to become more efficient and innovative in their teaching. Students lack confidence in approaching lecturers for assistance. Collaborative learning has stronger results and students believe in self-support to deal with their challenges based on their individual strengths. Collaborative learning is key to student academic performance.

Keywords: collaborative learning, consultations, student engagement, student performance

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

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Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

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Authors: Chloe L. Southern

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If play is deemed to fulfill children’s social, emotional, and physical domains, as well as satisfy their natural curiosity and promote self-reflexivity, it is difficult to understand why play is not prioritized to the same extent for older children. This paper explores and discusses the importance of play-based learning as well as the preliminary implications beyond the realm of kindergarten. To further extend the inquiry, discussions pertaining to play-based learning are looked at through the lens of relevant methodologies and theories. Different education systems are looked at in certain areas of the world that lead to curiosities not only towards their play-based practices and curriculum but what ideologies they have that set them apart.

Keywords: 21ˢᵗ century learning, play-based learning, student-centered learning, transformative learning

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Taiebe Shokri, Shahram Yazdani, Leila Afshar, Soleiman Ahmadi

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Introduction: The importance of professionalism in higher education not only determines the appropriate and inappropriate behaviors and guides faculty members in the implementation of professional responsibilities, but also guarantees faculty members' adherence to professional principles and values, ensures the quality of teaching and facilitator will be the teaching-learning process in universities and will increase the commitment to meet the needs of students as well as the development of an ethical culture based on ethics. Therefore, considering the important role of medical education teachers to prepare teachers and students in the future, the need to determine the concept of professional teacher and teacher, and the characteristics of teacher professionalism, we have explained the concept of professionalism in teachers in this study. Methods: The concept analysis method used in this study was Walker and Avant method which has eight steps. Walker and Avant state the purpose of concept analysis as follows: The process of distinguishing between the defining features of a concept and its unrelated features. The process of concept analysis includes selecting a concept, determining the purpose of the analysis, identifying the uses of the concept, determining the defining features of the concept, identifying a model, identifying boundary and adversarial items, identifying the precedents and consequences of the concept, and defining empirical references. is. Results: Professionalism in its general sense, requires deep knowledge, insight, creating a healthy and safe environment, honesty and trust, impartiality, commitment to the profession and continuous improvement, punctuality, criticism, professional competence, responsibility, and Individual accountability, especially in social interactions, is an effort for continuous improvement, the acquisition of these characteristics is not easily possible and requires education, especially continuous learning. Professionalism is a set of values, behaviors, and relationships that underpin public trust in teachers.

Keywords: concept analysis, medical education, professionalism, faculty members

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Authors: Jonathan H. Westover, Jacque P. Westover, Maureen S. Andrade

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Though learning theories vary in complexity and usefulness, a thorough understanding of foundational learning theories is a necessity in today’s educational environment. Additionally, learning theories lead to approaches in instruction that can affect student motivation and learning. The combination of a learning theory and elements to enhance student motivation can create a learning context where the student can thrive in their educational pursuits. This paper will provide an overview of three main learning theories: (1) Behavioral Theory, (2) Cognitive Theory, and (3) Constructivist Theory and explore their connection to elements of student learning motivation. Finally, we apply these learning theories and elements of student motivation to the following two context: (1) The FastStart Program at the Community College of Denver, and (2) An Online Academic English Language Course. We discussed potential of the program and course to have success in increasing student success outcomes.

Keywords: learning theory, student motivation, inclusive pedagogy, developmental education

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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Authors: Caterina Calicchio, Talia Sbardella

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The ability to move through geographical and symbolic spaces is key for building new nodes and social relationships. Especially in the framework of language learning, accepting and valuing diversity can help to create a constructive atmosphere of cooperation, innovation, and creativity. Thus, it is important to outline the stages of forming a learning community, focusing on the characteristics that can favor its development. It is known that elements like curiosity and motivation are significant for individual language learning; hence, the study attempts to investigate how factors like openness to diversity and cultural immersion could improve Italian learning and teaching. This paper aims to indicate the factors that could be significant for the development of a Learning Community by presenting a case study on a course on Italian as a second language for beginners: first, the theoretical matrices underlying social learning will be outlined. Secondly, a quantitative study will be described based on an adaptation of the openness to diversity and some insights psychometric scale questionnaire developed at the Umbra Institute. The questionnaire was delivered to 52 American college students with open-ended and closed-ended questions. Students were asked to specify their level of agreement to a set of statements on a six-point Likert scale ranging from (1) Strongly disagree to (6) Strongly agree. The data has been analyzed with a quantitative and qualitative method and has been represented in a pie chart and in a histogram. Moreover, mean and frequency have been calculated. The research findings demonstrate that openness to diversity and challenge enhances cross-cutting skills such as intercultural and communicative competence: through cultural immersion and the facility of speaking with locals, the participants have been able to develop their own Italian L2 language community. The goal is to share with the scientific community some insights to trace possible future lines of research.

Keywords: Italian as second language, language learning, learning community, openness to diversity

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Authors: Carla Teixeira, Diana Azevedo, Jonatas Bessa, Maria Guilam

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The flipped classroom is a blended learning modality that combines face-to-face and virtual activities of self-learning, mediated by digital information and communication technologies, which reverses traditional teaching approaches and presents, as a presupposition, the previous study of contents by students. In the following face-to-face activities, the contents are discussed, producing active learning. This work aims to describe the systematization process of the use of flipped classrooms as a method to develop complementary national activities in PROFSAÚDE, a professional master's program in the area of public health, offered as a distance learning course, in the network, in Brazil. The complementary national activities were organized with the objective of strengthening and qualifying students´ learning process. The network gathers twenty-two public institutions of higher education in the country. Its national coordination conducted a survey to detect complementary educational needs, supposed to improve the formative process and align important content sums for the program nationally. The activities were organized both asynchronously, making study materials available in Google classrooms, and synchronously in a tele presential way, organized on virtual platforms to reach the largest number of students in the country. The asynchronous activities allowed each student to study at their own pace and the synchronous activities were intended for deepening and reflecting on the themes. The national team identified some professors' areas of expertise, who were contacted for the production of audiovisual content such as video classes and podcasts, guidance for supporting bibliographic materials and also to conduct synchronous activities together with the technical team. The contents posted in the virtual classroom were organized by modules and made available before the synchronous meeting; these modules, in turn, contain “pills of experience” that correspond to reports of teachers' experiences in relation to the different themes. In addition, activity was proposed, with questions aimed to expose doubts about the contents and a learning challenge, as a practical exercise. Synchronous activities are built with different invited teachers, based on the participants 'discussions, and are the forum where teachers can answer students' questions, providing feedback on the learning process. At the end of each complementary activity, an evaluation questionnaire is available. The responses analyses show that this institutional network experience, as pedagogical innovation, provides important tools to support teaching and research due to its potential in the participatory construction of learning, optimization of resources, the democratization of knowledge and sharing and strengthening of practical experiences on the network. One of its relevant aspects was the thematic diversity addressed through this method.

Keywords: active learning, flipped classroom, network education experience, pedagogic innovation

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Authors: Mostafa Fanaei, Shahram R. Sistani, Athare Nazri-Panjaki

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Introduction: Critical thinking skills are increasingly recognized as vital for academic success, particularly in higher education. This study examines the influence of critical thinking on learning achievement among undergraduate and master's students enrolled in foreign language programs. By investigating this correlation, educators can gain valuable insights into optimizing teaching methodologies and enhancing academic outcomes. Methods: This cross-sectional study involved 150 students from the Shahid Bahonar University of Kerman, recruited via random sampling. Participants completed the Critical Thinking Questionnaire (CThQ), assessing dimensions such as analysis, evaluation, creation, remembering, understanding, and application. Academic performance was measured using the students' GPA (0-20). Results: The participants' mean age was 21.46 ± 5.2 years, with 62.15% being female. The mean scores for critical thinking subscales were as follows: Analyzing (13.2 ± 3.5), Evaluating (12.8 ± 3.4), Creating (18.6 ± 4.8), Remembering (9.4 ± 2.1), Understanding (12.9 ± 3.3), and Applying (12.5 ± 3.2). The overall critical thinking score was 79.4 ± 18.1, and the average GPA was 15.7 ± 2.4. Significant positive correlations were found between GPA and several critical thinking subscales: Analyzing (r = 0.45, p = 0.013), Creating (r = 0.52, p < 0.001), Remembering (r = 0.29, p = 0.021), Understanding (r = 0.41, p = 0.002), and the overall CThQ score (r = 0.54, p = 0.043). Conclusion: The study demonstrates a significant positive relationship between critical thinking skills and learning achievement in foreign language programs. Enhancing critical thinking skills through educational interventions could potentially improve academic performance. Further research is recommended to explore the underlying mechanisms and long-term impacts of critical thinking on academic success.

Keywords: critical thinking, learning achievement, higher education, foreign language programs, student success

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Authors: Zyra Cheska Hidalgo, Joehiza Mae Renon, Kzarina Buen, Girlie Mitrado

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ABSTRACT: The global coronavirus disease (COVID-19) has dramatically impacted the lives of many, including education and our economy. Thus, it presents a massive challenge for medical education as instructors are mandated to deliver their lectures virtually to ensure the continuity of the medical education process and ensure students' safety. The purpose of this research paper is to determine the lived experiences of paramedical students who are engaged in virtual hands-on learning and to determine the different coping strategies they used to deal with virtual hands-on learning. The researchers used the survey method of descriptive research design to determine the lived experiences and coping strategies of twenty (20) paramedical students from Lorma Colleges (particularly the College of Medicine Department). The data were collected through online questionnaires, particularly with the use of google forms. This study shows technical issues, difficulty in adapting styles, distractions and time management issues, mental and physical health issues, and lack of interest and motivation are the most common problems and challenges experienced by paramedical students. On the other hand, the coping strategies used by paramedical students to deal with those challenges include time management, engagement in leisure activities, acceptance of responsibilities, studying, and adapting. With the data gathered, the researchers concluded that virtual hands-on learning effectively increases the knowledge of paramedical students. However, teaching and learning barriers must have to be considered to implement virtual hands-on learning successfully.

Keywords: virtual hands-on learning, E-learning, paramedical students, medical education

Procedia PDF Downloads 123

Authors: Chingwen Yeh, Yu Ru Chen

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This paper aims to explore the growth and development of children in the creative dance class of Cloud Gate Dance School in Taichung Taiwan. Professor Chingwen Yeh’s qualitative research method was applied in this study. First of all, application of Dalcroze Eurhythmic teaching materials such as music, teaching aids, speaking language through classroom situation was collected and exam. Second, the in-class observation on the participation of the young children's learning situation was recorded both by words and on video screen as the research data. Finally, data analysis was categorized into the following aspects: children's body movement coordination, children’s mind concentration and imagination and children’s verbal expression. Through the in-depth interviews with the in-class teachers, parents of participating children and other in class observers were conducted from time to time; this research found the children's body rhythm, language skills, and social learning growth were improved in certain degree through the creative dance training. These authors hope the study can contribute as the further research reference on the related topic.

Keywords: Cloud Gate Dance School, creative dance, Dalcroze, Eurhythmic

Procedia PDF Downloads 290