Search results for: learning outcomes evaluation

Authors: Peng Wang, Tigang Jiang

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The computer based lip reading method of different languages cannot be universal. At present, for the research of Chinese lip reading, whether the work on data sets or recognition algorithms, is far from mature. In this paper, we study the Chinese lipreading method based on machine learning, and propose a Chinese Sentence-level lip-reading network (CNLipNet) model which consists of spatio-temporal convolutional neural network(CNN), recurrent neural network(RNN) and Connectionist Temporal Classification (CTC) loss function. This model can map variable-length sequence of video frames to Chinese Pinyin sequence and is trained end-to-end. More over, We create CNLRS, a Chinese Lipreading Dataset, which contains 5948 samples and can be shared through github. The evaluation of CNLipNet on this dataset yielded a 41% word correct rate and a 70.6% character correct rate. This evaluation result is far superior to the professional human lip readers, indicating that CNLipNet performs well in lipreading.

Keywords: lipreading, machine learning, spatio-temporal, convolutional neural network, recurrent neural network

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Authors: Khalak Bin Khair, Saqib Jahir, Mohammed Ibrahim, Fahad Bin, Debajyoti Karmaker

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Object detection is a computer technology that deals with searching through digital images and videos for occurrences of semantic elements of a particular class. It is associated with image processing and computer vision. On top of object detection, we detect camouflage objects within an image using Deep Learning techniques. Deep learning may be a subset of machine learning that's essentially a three-layer neural network Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into 4 categories to compare the result. Those images are labeled and then trained and tested using vgg16 architecture on the jupyter notebook using the TensorFlow platform. The architecture is further customized using Transfer Learning. Methods for transferring information from one or more of these source tasks to increase learning in a related target task are created through transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.

Keywords: deep learning, transfer learning, TensorFlow, camouflage, object detection, architecture, accuracy, model, VGG16

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Authors: Tasanee Satthapong

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The purpose of the study was to determine the relationship between learning style preferences, teaching style preferences, and learning with happiness of college students who were majors in five different academic areas at the Suansunandha Rajabhat University in Thailand. The selected participants were 729 students 1st year-5th year in Faculty of Education from Thai teaching, early childhood education, math and science teaching, and English teaching majors. The research instruments are the Grasha and Riechmann learning and teaching styles survey and the students’ happiness in learning survey, based on learning with happiness theory initiated by the Office of the National Education Commission. The results of this study: 1) The most students’ learning styles were participant style, followed by collaborative style, and independent style 2) Most students’ happiness in learning in all subjects areas were at the moderate level: Early Childhood Education subject had the highest scores, while Math subject was at the least scores. 3) No different of student’s happiness in learning were found between students who has learning styles that match and not match to teachers’ teaching styles.

Keywords: learning style, teaching style, learning with happiness

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Authors: Mohamed Jama Madar, Oso Wilis

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E-learning is the application of information technology in the teaching and learning process. This paper presents the Funnel model as a solution for the problems of implementation of e-learning in tertiary education institutions. While existing models such as TAM, theory-based e-learning and pedagogical model have been used over time, they have generally been found to be inadequate because of their tendencies to treat materials development, instructional design, technology, delivery and governance as separate and isolated entities. Yet it is matching components that bring framework of e-learning strategic implementation. The Funnel model enhances all these into one and applies synchronously and asynchronously to e-learning implementation where the only difference is modalities. Such a model for e-learning implementation has been lacking. The proposed Funnel model avoids ad-ad-hoc approach which has made other systems unused or inefficient, and compromised educational quality. Therefore, the proposed Funnel model should help tertiary education institutions adopt and develop effective and efficient e-learning system which meets users’ requirements.

Keywords: e-learning, pedagogical, technology, strategy

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Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

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Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

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Authors: Rattama Rattanawongsa

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As technologies continue to develop and evolve, online learning has become one of the most popular ways of gaining access to learning. Worldwide, many students are engaging in both online and blended courses in growing numbers through e-learning. However, online learning is a form of teaching that has many benefits for learners but still has some limitations. The high attrition rates of students tend to be due to lack of motivation to succeed. Gamification is the use of game design techniques, game thinking and game mechanics in non-game context, such as learning. The gamifying method can motivate students to learn with fun and inspire them to continue learning. This paper aims to describe how the gamification work in the context of learning. The first part of this paper present the concept of gamification. The second part is described the psychological perspectives of gamification, especially motivation and flow theory for gamifying design. The result from this study will be described into the guidelines for effective learning design using a gamification concept.

Keywords: gamification, e-learning, motivation, flow theory

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Authors: Sofia Hartati

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This research is aimed at describing training in early childhood education program empirically, describing teachers ability to plan lessons empirically, and acquiring empirical data as well as analyzing the influence of guided and independent training toward teachers competence in planning early childhood learning program. The method used is an experiment. It collected data with a population of 76 early childhood educators in Tunjung Teja Sub District area through random sampling technique and grouped into two namely 38 people in an experiment class and 38 people in a controlled class. The technique used for data collections is a test. The result of the research shows that there is a significant influence between training for guided educators toward Teachers Ability toward Planning Early Childhood Learning Program. Guided training has been proven to improve the ability to comprehend planning a learning program. The ability to comprehend planning a learning program owned by teachers of early childhood program comprises of 1) determining the characteristics and competence of students prior to learning; 2) formulating the objective of the learning; 3) selecting materials and its sequences; 4) selecting teaching methods; 5) determining the means or learning media; 6) selecting evaluation strategy as a part of teachers pedagogic competence. The result of this research describes a difference in the competence level of teachers who have joined guided training which is relatively higher than the teachers who joined the independent training. Guided training is one of an effective way to improve the knowledge and competence of early childhood educators.

Keywords: competence, planning, teachers, training

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Authors: Komon Paisal

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The purposes of this research were (1) to create a learning activity for constructivism, (2) study the Mathematical Analysis courses learning achievement, and (3) study students’ attitude toward the learning activity for constructivism. The samples in this study were divided into 2 parts including 3 Mathematical Analysis courses instructors of Suan Sunandha Rajabhat University who provided basic information and attended the seminar and 17 Mathematical Analysis courses students who were studying in the academic and engaging in the learning activity for constructivism. The research instruments were lesson plans constructivism, subjective Mathematical Analysis courses achievement test with reliability index of 0.8119, and an attitude test concerning the students’ attitude toward the Mathematical Analysis courses learning activity for constructivism. The result of the research show that the efficiency of the Mathematical Analysis courses learning activity for constructivism is 73.05/72.16, which is more than expected criteria of 70/70. The research additionally find that the average score of learning achievement of students who engaged in the learning activities for constructivism are equal to 70% and the students’ attitude toward the learning activity for constructivism are at the medium level.

Keywords: constructivism, learning management, mathematics analysis courses, learning activity

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Authors: Matthew Montebello

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The way e-learning effectiveness has been notoriously measured within an academic setting is by comparing the e-learning medium to the traditional face-to-face teaching methodology. In this paper, a simple yet innovative comparison methodology is introduced, whereby the effectiveness of next generation e-learning systems are assessed in contrast not only to the face-to-face mode, but also to the classical e-learning modality. Ethical and logistical issues are also discussed, as this three-way approach to compare teaching methodologies was applied and documented in a real empirical study within a higher education institution.

Keywords: e-learning effectiveness, higher education, teaching modality comparison

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Henriette van Rensburg, Betty Adcock

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Concern about the lack of knowledge of quality teaching and teacher retention in rural and remote areas of Australia, has caused academics to improve pre-service teachers’ understanding of this problem. The participants in this study were forty students enrolled in an undergraduate educational course (EDO3341 Teaching in rural and remote communities) at the University of Southern Queensland in Toowoomba in 2012. This study involved an innovative case-based teaching approach in order to broaden their generally under-informed understanding of teaching in a rural and remote area. Three themes have been identified through analysing students’ critical reflections: learning expertise, case-based learning support and authentic learning. The outcomes identified the changes in pre-service teachers’ understanding after they have deepened their knowledge of the realities of teaching in rural and remote areas.

Keywords: rural and remote education, case based teaching, innovative education approach, higher education

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Authors: Leena Alfarani

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Although mobile devices are ubiquitous on university campuses, teacher-readiness for mobile learning has yet to be fully explored in the non-western nations. This study shows that two main factors affect the adoption and use of m-learning among female teachers within a university in Saudi Arabia—resistance to change and perceived social culture. These determinants of the current use and intention to use of m-learning were revealed through the analysis of an online questionnaire completed by 165 female faculty members. This study reveals several important issues for m-learning research and practice. The results further extend the body of knowledge in the field of m-learning, with the findings revealing that resistance to change and perceived social culture are significant determinants of the current use of and the intention to use m-learning.

Keywords: blended learning, mobile learning, technology adoption, devices

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Authors: Rong Guo, Mengshi Huang, Yujing Bai

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With the rapid development of urbanization, the urban population increases and urban sprawl appeared. And these issues led to a sharp deterioration of the ecological environment. So, the urban ecological security evaluation was imminent. The weights identify of index was a key step of the research of ecological security evaluation. The AHP was widely used in the extensive research of weights identify of ecological security index. The characteristics of authority and quantitative can fully reflect the views of relevant experts. On the basis of building the ecological security evaluation index of Harbin, the paper combed and used the basic principle of the AHP, and calculated the weights of Harbin ecological security evaluation index through the process of the expert opinions “summary-feedback-summary”. And lay a foundation of future study of Harbin ecological security index, and guide the quantitative evaluation of Harbin ecological security.

Keywords: AHP, ecological security, evaluation Index, weights identify, harbin

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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Authors: Muhammad Nawaz, Sandeep N. Kundu, Farha Sattar

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Augmented reality sandbox adds new dimensions to education and learning process. It can be a core component of geoscience teaching and learning to understand the geographic contexts and landform processes. Augmented reality sandbox is a useful tool not only to create an interactive learning environment through spatial visualization but also it can provide an active learning experience to students and enhances the cognition process of learning. Augmented reality sandbox can be used as an interactive learning tool to teach geomorphic and landform processes. This article explains the augmented reality sandbox and the constructivism approach for geoscience teaching and learning, and endeavours to explore the ways to teach the geographic processes using the three-dimensional digital environment for the deep learning of the geoscience concepts interactively.

Keywords: augmented reality sandbox, constructivism, deep learning, geoscience

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Authors: Nassim Dennouni, Yvan Peter, Luigi Lancieri, Zohra Slama

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The objective of this article is to make a bibliographic study on the recommendation of mobile learning activities that are used as part of the field trip scenarios. Indeed, the recommendation systems are widely used in the context of mobility because they can be used to provide learning activities. These systems should take into account the history of visits and teacher pedagogy to provide adaptive learning according to the instantaneous position of the learner. To achieve this objective, we review the existing literature on field trip scenarios to recommend mobile learning activities.

Keywords: mobile learning, field trip, mobile learning activities, collaborative filtering, recommendation system, point of interest, ACO algorithm

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Authors: Prajwal Prakash Vasisht, Sharath Rajamurthy, Nishanth Dara

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In a supervised machine learning approach, metrics such as precision, accuracy, and coverage can be calculated using ground truth labels to help in model tuning, evaluation, and selection. In an unsupervised setting, however, where the data has no ground truth, there are few interpretable metrics that can guide us to do the same. Our approach creates a framework to adapt the Intersection over Union metric, referred to as Adapted IoU, usually used to evaluate supervised learning models, into the unsupervised domain, which solves the problem by factoring in subject matter expertise and intuition about the ideal output from the model. This metric essentially provides a scale that allows us to compare the performance across numerous unsupervised models or tune hyper-parameters and compare different versions of the same model.

Keywords: general metric, unsupervised learning, classification, intersection over union

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Authors: Zhi Huang

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This study follows on from previous survey and focus group research exploring the effective teaching process in a translation classroom in Australian universities through case study method. The data analysis draws on social constructivist theory in translation teaching and focuses on teaching process aiming to discover how effective translation teachers conduct teaching in the classroom. The results suggest that effective teaching requires the teacher to have ability in four aspects: classroom management, classroom pedagogy, classroom communication, and teacher roles. Effective translation teachers are able to control the whole learning process, facilitate students in independent learning, guide students to be more critical about translation, giving both positive and negative feedback for students to reflect on their own, and being supportive, patient and encouraging to students for better classroom communication and learning outcomes. This study can be applied to other teachers in translation so that they can reflect on their own teaching in their education contexts and strive for being a more qualified translation teacher and achieving teaching effectiveness.

Keywords: case study, classroom observation, classroom teaching, effective translation teaching, teacher effectiveness

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Authors: Kherafa Abdennasser

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The application of Information and Communication Technologies (ICT) to the training area led to the creation of this new reality called E-learning. That last one is described like the marriage of multi- media (sound, image and text) and of the internet (diffusion on line, interactivity). Distance learning became an important totality for training and that last pass in particular by the setup of a distance learning platform. In our memory, we will use an open source platform named Dokeos for the management of a distance training of GPS called e-GPS. The learner is followed in all his training. In this system, trainers and learners communicate individually or in group, the administrator setup and make sure of this system maintenance.

Keywords: ICT, E-learning, learning plate-forme, Dokeos, GPS

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Authors: Eric Morettin

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Cybersecurity and digital literacy are pressing issues among Canadian citizens, yet formal education does not provide today’s students with the necessary knowledge and skills needed to adapt to these challenging issues within the physical and digital labor-market. Canada’s current education systems do not highlight the importance of these respective fields, aside from using technology for learning management systems and alternative methods of assignment completion. Educators are not properly trained to integrate technology into the compulsory courses within public education, to better prepare their learners in these topics and Canada’s digital economy. ICTC addresses these gaps in education and training through cross-Canadian educational programming in digital literacy and competency, cybersecurity and coding which is bridged with Canada’s provincially regulated K-12 curriculum guidelines. After analyzing Canada’s provincial education, it is apparent that there are gaps in learning related to technology, as well as inconsistent educational outcomes that do not adequately represent the current Canadian and global economies. Presently only New Brunswick, Nova Scotia, Ontario, and British Columbia offer curriculum guidelines for cybersecurity, computer programming, and digital literacy. The remaining provinces do not address these skills in their curriculum guidelines. Moreover, certain courses across some provinces not being updated since the 1990’s. The three territories respectfully take curriculum strands from other provinces and use them as their foundation in education. Yukon uses all British Columbia curriculum. Northwest Territories and Nunavut respectfully use a hybrid of Alberta and Saskatchewan curriculum as their foundation of learning. Education that is provincially regulated does not allow for consistency across the country’s educational outcomes and what Canada’s students will achieve – especially when curriculum outcomes have not been updated to reflect present day society. Through this, ICTC has aligned Canada’s provincially regulated curriculum and created opportunities for focused education in the realm of technology to better serve Canada’s present learners and teachers; while addressing inequalities and applicability within curriculum strands and outcomes across the country. As a result, lessons, units, and formal assessment strategies, have been created to benefit students and teachers in this interdisciplinary, cross-curricular, practice - as well as meeting their compulsory education requirements and developing skills and literacy in cyber education. Teachers can access these lessons and units through ICTC’s website, as well as receive professional development regarding the assessment and implementation of these offerings from ICTC’s education coordinators, whose combines experience exceeds 50 years of teaching in public, private, international, and Indigenous schools. We encourage you to take this opportunity that will benefit students and educators, and will bridge the learning and curriculum gaps in Canadian education to better reflect the ever-changing public, social, and career landscape that all citizens are a part of. Students are the future, and we at ICTC strive to ensure their futures are bright and prosperous.

Keywords: cybersecurity, education, curriculum, teachers

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Authors: AnjalI A. Prasad

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Nowadays, social media played an important role in spreading misinformation or fake news. This study analyzes the fake news related to the COVID-19 pandemic spread in social media. This paper aims at evaluating and comparing different approaches that are used to mitigate this issue, including popular deep learning approaches, such as CNN, RNN, LSTM, and BERT algorithm for classification. To evaluate models’ performance, we used accuracy, precision, recall, and F1-score as the evaluation metrics. And finally, compare which algorithm shows better result among the four algorithms.

Keywords: BERT, CNN, LSTM, RNN

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Authors: Salihu Abdullahi Galle

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Students' performance in Economics in schools and on standardized exams in Nigeria has been worrying throughout the years, owing to some teachers' use of conventional and lecture teaching methods. Other obstacles include a lack of training, standardized testing pressure, and aversion to change, all of which can have an impact on students' cognitive ability in Economics and future careers. The researchers employed formative evaluation with feedback (FEFB) to support the teaching and learning process by providing constant feedback to both teachers and students. The researchers employed a quasi-experimental research design to examine two teaching methods (FEFB and traditional). The pre-test and post-test interaction effects were evaluated between students in the experimental group (FEFB) and those in the conventional group. The interaction effects of pre-test and post-test on male and female in the two groups were also examined, with 90 participants. The findings show that students exposed to a FEFB-based teaching approach outperform pupils taught in a traditional classroom setting, and there is no gender interaction effect between the two groups. In light of these findings, the researchers urge that Economics teachers employ FEFB during teaching and learning to ensure timely feedback, and that policymakers ensure that Economics teachers receive training and re-training on FEFB approaches.

Keywords: formative evaluation with feedback (FEFB), students, economics achievement, secondary education

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Authors: Y. Kim, H. Lee, M. Park, B. Lee

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Planning is understood as the determination of what has to be performed, how, in which sequence, when, what resources are needed, and their cost within the organization before execution. In most construction project, it is evident that the inherent nature of planning is dynamic, and initial planning is subject to be changed due to various uncertain conditions of construction project. Planners take a continuous revision process during the course of a project and until the very end of project. However, current practice lacks reliable, systematic tool for setting variance thresholds to determine when and what corrective actions to be taken. Rather it is heavily dependent on the level of experience and knowledge of the planner. Thus, this paper introduces a machine learning approach to evaluate project control threshold reliability incorporating project-specific data and presents a method to automate the process. The results have shown that the model improves the efficiency and accuracy of the monitoring process as an early warning.

Keywords: machine learning, project control, project progress monitoring, schedule

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Authors: David Lynch, Jake Madden

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There exists a body of literature that reports on the many benefits of partnerships between universities and schools, especially in terms of teaching improvement and school reform. This is because such partnerships can build significant teaching capital, by deepening and expanding the skillsets and mindsets needed to create the connections that support ongoing and embedded teacher professional development and career goals. At the same time, this literature is critical of such initiatives when the partnership outcomes are short- term or one-sided, misaligned to fundamental problems, and not expressly focused on building the desired teaching capabilities. In response to this situation, research conducted by Professor David Lynch and his TeachLab research team, has begun to shed light on the strengths and limitations of school/university partnerships, via the identification of key conceptual elements that appear to act as critical partnership success factors. These elements are theorised as an inter-play between professional knowledge acquisition, readiness, talent management and organisational structure. However, knowledge of how these elements are established, and how they manifest within the school and its teaching workforce as an overall system, remains incomplete. Therefore, research designed to more clearly delineate these elements in relation to their impact on school/university partnerships is thus required. It is within this context that this paper reports on the development and testing of a Professional Learning (PL) model for schools and their teachers that incorporates school-university research partnering within a systematic, whole-of-school PL strategy that is underpinned and structured by a micro-credentialing (MC) regime. MC involves learning a narrow-focused certificate (a micro-credential) in a specific topic area (e.g., 'How to Differentiate Instruction for English as a second language Students') and embedded in the teacher’s day-to-day teaching work. The use of MC is viewed as important to the efficacy and sustainability of teacher PL because it (1) provides an evidence-based framework for teacher learning, (2) has the ability to promote teacher social capital and (3) engender lifelong learning in keeping professional skills current in an embedded and seamless to work manner. The associated research is centred on a primary school in Australia (P-6) that acted as an arena to co-develop, test/investigate and report on outcomes for teacher PL that uses MC to support a whole-of-school partnership with a university.

Keywords: teaching improvement, teacher professional learning, talent management, education partnerships, school-university research

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Authors: Nitin Shravan, Sudarsun Santhiappan, B. Sivaselvan

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Subsection identification, in the context of Electronic Health Records (EHRs), is identifying the important sections for down-stream tasks like auto-coding. In this work, we classify the text present in EHRs according to their information, using machine learning and deep learning techniques. We initially describe briefly about the problem and formulate it as a text classification problem. Then, we discuss upon the methods from the literature. We try two approaches - traditional feature extraction based machine learning methods and deep learning methods. Through experiments on a private dataset, we establish that the deep learning methods perform better than the feature extraction based Machine Learning Models.

Keywords: deep learning, machine learning, semantic clinical classification, subsection identification, text classification

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Authors: Mohamed Bendahmane, Brahim Elfalaki, Mohammed Benattou

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One of the major sources of learners' professional difficulties is their heterogeneity. Whether on cognitive, social, cultural or emotional level, learners being part of the same group have many differences. These differences do not allow to apply the same learning process at all learners. Thus, an optimal learning path for one, is not necessarily the same for the other. We present in this paper a model-oriented service to offer to each learner a personalized learning path to acquire the targeted skills.

Keywords: learning path, web service, trace analysis, personalization

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Authors: Meredith Jones, Susan Catapano, Carol McNulty

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Study abroad experiences create unique learning opportunities for preservice teachers to strengthen their reflective thinking practices through applied learning experiences. Not only do study abroad experiences provide opportunities for students to expand their cultural sensitivity, but incorporating applied learning experiences in study abroad trips creates unique opportunities for preservice teachers to engage in critical reflection on their teaching skills. Applied learning experiences are designed to nurture learning and growth through a reflective, experiential process outside the traditional classroom setting. As students participate in applied learning experiences, they engage in critical reflection independently, with their peers, and with university faculty. Critical reflection within applied learning contexts generates, deepens, and documents learning but must be intentionally designed to be effective. Grounded in Dewey’s model of reflection, this qualitative study examines longitudinal data from various study abroad cohorts from a particular university. Reflective data was collected during the study abroad trip, and follow up data on critical reflection of teaching practices were collected six months and a year after the trip. Dewey’s model of reflection requires preservice teachers to make sense of their experiences by reflecting on theoretical knowledge, experiences, and pedagogical knowledge. Guided reflection provides preservice teachers with a framework to respond to questions and ideas critical to the applied learning outcomes. Prompts are used to engage preservice teachers in reflecting on situations they have experienced and how they can be transferred to their teaching. Findings from this study noted that students with previous field experiences, or work in the field, engaged in more critical reflection on pedagogical knowledge throughout their applied learning experience. Preservice teachers with limited experiences in the field benefited from engaging in critical reflection prompted by university faculty during the applied learning experience. However, they were able to independently engage in critical reflection once they began work in the field through university field placements, internships, or student teaching. Finally, students who participated in study abroad applied learning experiences reported their critical reflection on their teaching practices, and cultural sensitivity enhanced their teaching and relationships with children once they formally entered the teaching profession.

Keywords: applied learning experiences, critical reflection, cultural sensitivity, preservice teachers, teacher education

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Authors: Omran Alharbi

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It is difficult to find an aspect of our modern lives that has been untouched by mobile technology. Indeed, the use of mobile learning in Saudi Arabia may enhance students’ learning and increase overall educational standards. However, within tertiary education, the success of e-learning implementation depends on the degree to which students and educators accept mobile learning and are willing to utilise it. Therefore, this research targeted the factors that influence Hail University instructors’ intentions to use mobile learning. An online survey was completed by eighty instructors and it was found that their use of mobile learning was heavily predicted by performance experience, effort expectancy, social influence, and facilitating conditions; the multiple regression analysis revealed that 67% of the variation was accounted for by these variables. From these variables, effort expectancy was shown to be the strongest predictor of intention to use e-learning for instructors.

Keywords: acceptance, faculty member, mobile learning, KSA

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Authors: Marina Vicario, Amadeo Argüelles, Pilar Gómez, Carlos Hernández

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In this paper, the Computer Research Network of the National Polytechnic Institute of Mexico proposes a paradigmatic model for the inference of cognitive patterns in digital learning systems. This model leads to metadata architecture useful for analysis and prediction in online learning systems; especially on MOOc's architectures. The model is in the design phase and expects to be tested through an institutional of courses project which is going to develop for the MOOc.

Keywords: cognitive footprints, learning analytics, predictive learning, digital learning, educational computing, educational informatics

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Authors: Flavio Campos, Patricia Masmo, Fernanda Yamamoto

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The report presents a research about teaching professional competencies through projects, considering the student as an active learner and curriculum development. Considering project based-learning, the report articulate the result of research about curriculum development for professional competencies and teaching-learning strategies to help the development of professional competencies in learning environments in the courses of National Learning Service in São Paulo, Brazil. There so, intend to demonstrate fundamentals to elaborate curriculum to learning environment, specific about teaching methodologies to enrich student-learning process, using projects. The practice that has been taking place since 2013 indicates the needs of rethinking knowledge and practice in courses that prepared students to labor.

Keywords: curriculum design, active learning, professional competencies, project based-learning

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