Search results for: learning outcomes assessment

Authors: Luz Janeth Ospina M.

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The fourth industrial revolution is changing the role of education substantially and, therefore, the role of instructors and learners at all levels. Education 4.0 is an imminent response to the needs of a globalized world where humans and technology are being aligned to enable endless possibilities, among them the need for students, as digital natives, to communicate effectively in at least one language besides their mother tongue, and also the requirement of developing theirs. This is an exploratory study in which a control group (N = 21), all of the students of Spanish as a foreign language at the university level, after taking a Spanish class, responded to an online questionnaire about the engagement, atmosphere, and environment in which their course was delivered. These aspects considered in the survey were relative to the instructor’s teaching style, including: (a) active, hands-on learning; (b) flexibility for in-class activities, easily switching between small group work, individual work, and whole-class discussion; and (c) integrating technology into the classroom. Strongly believing in these principles, the instructor deliberately taught the course in a SCALE-UP room, as it could facilitate such a positive and encouraging learning environment. These aspects are trends related to Education 4.0 and have become integral to the instructor’s pedagogical stance that calls for a constructive-affective role, instead of a transmissive one. As expected, with a learning environment that (a) fosters student engagement and (b) improves student outcomes, the subjects were highly engaged, which was partially due to the learning environment. An overwhelming majority (all but one) of students agreed or strongly agreed that the atmosphere and the environment were ideal. Outcomes of this study are relevant and indicate that it is about time for teachers to build up a meaningful correlation between humans and technology. We should see the trends of Education 4.0 not as a threat but as practices that should be in the hands of critical and creative instructors whose pedagogical stance responds to the needs of the learners in the 21st century.

Keywords: active learning, education 4.0, higher education, pedagogical stance

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Authors: Adelia Desi Agnesita

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The advent of a new disease called covid-19 made many major changes in the world, one of which is the process of learning and teaching. Learning formerly offline but now is done online, which makes students need adaptation to the learning process. The covid-19 pandemic that occurs almost worldwide causes activities that involve many people to be avoided, one of which is learning to teach. In Indonesia, since March 2020, the process of college learning is turning into online/ long-distance learning. It's to prevent the spread of the covid-19. Student online learning presents some of the obstacles to poor signals, many of the tasks, lack of focus, difficulty sleeping, and resulting stress.

Keywords: learning, online, covid-19, pandemic

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Authors: Heikki Valmu, Eero Kupila, Raisa Vartia

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A major curricular reform was implemented in Metropolia UAS in 2014. The teaching was to be based on larger course entities and collaborative pedagogy. The most thorough reform was conducted in the department of electrical engineering and automation technology. It has been already shown that the reform has been extremely successful with respect to student progression and drop-out rate. The improvement of the results has been much more significant in this department compared to the other engineering departments making only minor pedagogical changes. In the beginning of the spring term of 2017, a thorough student feedback project was conducted in the department. The study consisted of thirty questions about the implementation of the curriculum, the student workload and other matters related to student satisfaction. The reply rate was more than 40%. The students were divided to four different categories: first year students [cat.1] and students of all the three different majors [categories 2-4]. These categories were found valid since all the students have the same course structure in the first two semesters after which they may freely select the major. All staff members are divided into four teams respectively. The curriculum consists of consecutive 15 credit (ECTS) courses each taught by a group of teachers (3-5). There are to be no end exams and continuous assessment is to be employed. In 2014 the different teacher groups were encouraged to employ innovatively different assessment methods within the given specs. One of these methods has been since used in categories 1 and 2. These students have to complete a number of compulsory tasks each week to pass the course and the actual grade is defined by a smaller number of tests throughout the course. The tasks vary from homework assignments, reports and laboratory exercises to larger projects and the actual smaller tests are usually organized during the regular lecture hours. The teachers of the other two majors have been pedagogically more conservative. The student progression has been better in categories 1 and 2 compared to categories 3 and 4. One of the main goals of this survey was to analyze the reasons for the difference and the assessment methods in detail besides the general student satisfaction. The results show that in the categories following more strictly the specified assessment model much more versatile assessment methods are used and the basic spirit of the new pedagogy is followed. Also, the student satisfaction is significantly better in categories 1 and 2. It may be clearly stated that continuous assessment and teacher cooperation improve the learning outcomes, student progression as well as student satisfaction. Too much academic freedom seems to lead to worse results [cat 3 and 4]. A standardized assessment model is launched for all students in autumn 2017. This model is different from the one used so far in categories 1 and 2 allowing more flexibility to teacher groups, but it will force all the teacher groups to follow the general rules in order to improve the results and the student satisfaction further.

Keywords: continuous assessment, course integration, curricular reform, student feedback

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Authors: Martin Dupuy, Solange Grunenwald, Pierre-Louis Colombo, Laurence Mahieu, Pomone Richard, Philippe Bartoli

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Endonasal endoscopic trans-sphenoidal surgery for pituitary tumours has become a mainstay of treatment over the last two decades. Although it is generally accepted that there is no significant difference between endoscopic versus microscopic approach for surgical outcomes (endocrine and ophthalmologic status), nasal morbidity seems to the benefit of endoscopic procedures. Minimally invasive endoscopic surgery needs an operative learning curve to achieve surgeon’s efficiency. This learning curve is now well known for surgical outcomes and complications rate, however, few data are available for nasal morbidity. The aim of our series is to document operative experience and nasal quality of life after (NQOL) endoscopic trans-sphenoidal surgery. The prospective pituitary surgical cohort consisted of 525 consecutives patients referred to our Skull Base Diseases Department. Endoscopic procedures were performed by a single neurosurgeon using an uninostril approach. NQOL was evaluated using the Sino-Nasal Test (SNOT-22), the Anterior Base Nasal Inventory (ASBNI) and the Skull Base Inventory Score (SBIS). Data were collected before surgery during hospital stay and 3 months after the surgery. The seventy first patients were compared to the latest 70 patients. There was no significant difference between comparison score before versus after surgery for SNOT-22, ASBNI and SBIS during the single surgeon’s learning curve. Our series demonstrates that in our institution there is no statistically significant learning curve for NQOL after uninostril endoscopic pituitary surgery. A careful progression through sinonasal structures with very limited mucosal incision is associated with minimal morbidity and preserves nasal function. Conservative and minimal invasive approach could be achieved early during learning curve.

Keywords: pituitary surgery, quality of life, minimal invasive surgery, learning curve, pituitary tumours, skull base surgery, endoscopic surgery

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Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: Youmen Chaaban, Abdallah Abu-Tineh

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This article examines the development of a professional development (PD) model for educator growth and learning that is embedded into the school context. The School based Support Program (SBSP), designed for the Qatari context, targets the practices, knowledge, and skills of both school leadership and teachers in an attempt to improve students’ learning outcomes. Key aspects of the model include the development of learning communities among teachers, strong leadership that supports school improvement activities, and the use of research-based PD to improve teacher practices and student achievement. This paper further presents the results of a qualitative study examining the perceptions of nineteen instructional coaches about the strengths of the PD program, the challenges they face in their day-to-day implementation of the program, and their suggestions for the betterment of the program’s implementation and outcomes. Data were collected from the instructional coaches through open-ended surveys followed by focus group interviews. The instructional coaches reported several strengths, which were compatible with the literature on effective PD. However, the challenges they faced were deeply rooted within the structure of the program, in addition to external factors operating at the school and Ministry of Education levels. Thus, a general consensus on the way the program should ultimately develop was reached.

Keywords: situated professional development, school reform, instructional coach, school based support program

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Authors: Shirly May Balais

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This study aims to evaluate the effects of vocabulary instruction in improving the students’ learning in science. The teacher-researcher utilized the vocabulary instructional materials in enriching the science vocabulary of grade four learners. The students were also given an achievement test to determine the effects of vocabulary instructional materials. The assessment indicated that students had shown improvement in comprehension and science literacy. This also helps the students to grasp, understand, and communicate appropriate science concepts and the integration of imagery makes learning science fun. In this research, descriptive qualitative methods and observation interviews were used to describe the effects of using vocabulary instructional materials in improving the science vocabulary of grade four learners. The students’ perceptions were studied, analyzed, and interpreted qualitatively.

Keywords: instruction, learning, science, vocabulary

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Authors: Eyup Bayram Guzel

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There have been growing awareness that technology offers unique and promising advantages by offering up-to-data educational materials in promoting teaching and learning materials, new strategies for building enhanced communication environment for people with disabilities and specifically for this study concentrated on the students with deafness and hearing impairments. Creating e-learning environment where teachers and students work in collaboration to develop better educational outcomes is the foremost reason of conducting this research. This study examined the perspectives of special education teachers’ regarding an application of e-learning software called Multimedia Builder on the students with deafness and hearing impairments. Initial and follow up interviews were conducted with 15 special education teachers around the scope of qualitative case study. Grounded approach has been used to analyse and interpret the data. The research results revealed that application of Multimedia Builder software were influential on reading, sign language, vocabulary improvements, computer and ICT usage developments and on audio-visual learning achievements for the advantages of students with deafness and hearing impairments. The implications of the study encouraged the ways of using e-learning tools and strategies to promote unique and comprehensive learning experiences for the targeted students and their teachers.

Keywords: e-learning, special education, deafness and hearing impairment, computer-ICT usage.

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Authors: Cristy Stagnar, Nina Hubig, Diana Ivankovic

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The epigenome is a compelling candidate for mediating long-term responses to environmental effects modifying disease risk. The main goal of this research is to develop a machine learning-based DNA methylation score, which will be valuable in delineating the unique contribution of paternal epigenetic modifications to the germline impacting childhood health outcomes. It will also be a useful tool in validating self-reports of nonsmoking and in adjusting epigenome-wide DNA methylation association studies for this early-life exposure. Using secondary data from two population-based methylation profiling studies, our DNA methylation score is based on CpG DNA methylation measurements from cord blood gathered from children whose fathers smoked pre- and peri-conceptually. Each child’s mother and father fell into one of three class labels in the accompanying questionnaires -never smoker, former smoker, or current smoker. By applying different machine learning algorithms to the accessible resource for integrated epigenomic studies (ARIES) sub-study of the Avon longitudinal study of parents and children (ALSPAC) data set, which we used for training and testing of our model, the best-performing algorithm for classifying the father smoker and mother never smoker was selected based on Cohen’s κ. Error in the model was identified and optimized. The final DNA methylation score was further tested and validated in an independent data set. This resulted in a linear combination of methylation values of selected probes via a logistic link function that accurately classified each group and contributed the most towards classification. The result is a unique, robust DNA methylation score which combines information on DNA methylation and early life exposure of offspring to paternal smoking during pregnancy and which may be used to examine the paternal contribution to offspring health outcomes.

Keywords: epigenome, health outcomes, paternal preconception environmental exposures, supervised machine learning

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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Authors: Patrick Mapulanga, Chisomo Petros Ganya

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Purpose: This study aimed to investigate the integration of Simulation-Based Education (SBE) into nursing and midwifery curricula in resource-constrained countries using Malawi as a case study. The purpose of this study is to assess the extent to which SBE is mentioned in curricula and explore the associated content, assessment criteria, and guidelines. Methodology: The research methodology involved a desk study of nursing and midwifery curricula in Malawi. A comprehensive review was conducted to identify references to SBE by examining documents such as official curriculum guides, syllabi, and educational policies. The focus is on understanding the prevalence of SBE without delving into the specific content or assessment details. Findings: The findings revealed that SBE is indeed mentioned in the nursing and midwifery curricula in Malawi; however, there is a notable absence of detailed content and assessment criteria. While acknowledgement of SBE is a positive step, the lack of specific guidelines poses a challenge to its effective implementation and assessment within the educational framework. Conclusion: The study concludes that although the recognition of SBE in Malawian nursing and midwifery curricula signifies a potential openness to innovative learning strategies, the absence of detailed content and assessment criteria raises concerns about the practical application of SBE. Addressing this gap is crucial for harnessing the full transformative potential of SBE in resource-constrained environments. Areas for Further Research: Future research endeavours should focus on a more in-depth exploration of the content and assessment criteria related to SBE in nursing and midwifery curricula. Investigating faculty perspectives and students’ experiences with SBE could provide valuable insights into the challenges and opportunities associated with its implementation. Study Limitations and Implications: The study's limitations include reliance on desk-based analysis, which limits the depth of understanding regarding SBE implementation. Despite this constraint, the implications of the findings underscore the need for curriculum developers, educators, and policymakers to collaboratively address the gaps in SBE integration and ensure a comprehensive and effective learning experience for nursing and midwifery students in resource-constrained countries.

Keywords: simulation based education, transformative learning, nursing and midwifery, curricula, Malawi

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Authors: Ethan James

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Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

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Authors: Yessica A. Aguilera

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English is currently the only foreign language included in the national educational curriculum in Chile. The English curriculum establishes that once completed secondary education, students are expected to reach B1 level according to the Common European Reference Framework (CEFR) scale. However, the objective has not been achieved, and to the author’s best knowledge, there is still a severe lack of English language skills among students who have completed their secondary education studies. In order to deal with the fact that students do not manage English as expected, team-based learning (TBL) was introduced in English language lessons at the Universidad Federico Santa María (USM). TBL is a collaborative teaching-learning method which enhances active learning by combining individual and team work. This approach seeks to help students achieve course objectives while learning how to function in teams. The purpose of the research was to assess the implementation and effectiveness of TBL in English language classes at USM technical training education. Quantitative and qualitative data were collected from teachers and students about their experience through TBL. Research findings show that both teachers and students are satisfied with the method and that students’ engagement and participation in class is higher. Additionally, students score higher on examinations improving academic outcomes. The findings of the research have the potential to guide how TBL could be included in future English language courses.

Keywords: collaborative learning, college education, English language learning, team-based learning

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Authors: Ade Dwi Utami

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Pedagogic competence is the basic competence of teachers to perform their tasks as educators. The ability to assess has become one of the demands in teachers pedagogic competence. Teachers ability to assess is related to curriculum instructions and applications. This research is aimed at obtaining data concerning teachers ability to assess that comprises of understanding assessment, determining assessment type, tools and procedure, conducting assessment process, and using assessment result information. It uses mixed method of explanatory technique in which qualitative data is used to verify the quantitative data obtained through a survey. The technique of quantitative data collection is by test whereas the qualitative data collection is by observation, interview and documentation. Then, the analyzed data is processed through a proportion study technique to be categorized into high, medium and low. The result of the research shows that teachers ability to assess can be grouped into 3 namely, 2% of high, 4% of medium and 94% of low. The data shows that teachers ability to assess is still relatively low. Teachers are lack of knowledge and comprehension in assessment application. The statement is verified by the qualitative data showing that teachers did not state which aspect was assessed in learning, record children’s behavior, and use the data result as a consideration to design a program. Teachers have assessment documents yet they only serve as means of completing teachers administration for the certification program. Thus, assessment documents were not used with the basis of acquired knowledge. The condition should become a consideration of the education institution of educators and the government to improve teachers pedagogic competence, including the ability to assess.

Keywords: assessment, early childhood education, pedagogic competence, teachers

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Authors: Netanel Stern

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Artificial intelligence (AI) algorithms have emerged as powerful tools in the field of psychiatry, offering new possibilities for enhancing diagnosis and treatment outcomes. This article explores the utilization of AI algorithms in psychiatry, highlighting their potential to revolutionize patient care. Various AI algorithms, including machine learning, natural language processing (NLP), reinforcement learning, clustering, and Bayesian networks, are discussed in detail. Moreover, ethical considerations and future directions for research and implementation are addressed.

Keywords: AI, software engineering, psychiatry, neuroimaging

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Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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Authors: Rochelle Elva

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Faculty in Higher Education today are faced with the challenge of convincing their students of the importance of learning and mastery of skills. This is because most students often have a single motivation -to get high grades. If it appears that this goal will not be met, they lose their motivation, and their academic efforts wane. This is true even for students in the competitive fields of STEM, including Computer Science majors. As educators, we have to understand our students and leverage what motivates them to achieve our learning outcomes. This paper presents a case study that utilizes cognitive psychology’s Expectancy Value Theory and Motivation Theory to investigate the effect of sustained expectancy for success on students’ learning outcomes. In our case study, we explore how students’ motivation and persistence in their academic efforts are impacted by providing them with an unexpected possible path to success that continues to the end of the semester. The approach was tested in an undergraduate computer science course with n = 56. The results of the study indicate that when presented with the real possibility of success, despite existing low grades, both low and high-scoring students persisted in their efforts to improve their performance. Their final grades were, on average, one place higher on the +/-letter grade scale, with some students scoring as high as three places above their predicted grade.

Keywords: expectancy for success and persistence, motivation and performance, computer science education, motivation and performance in computer science

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Authors: Nur Azlina Mohamed Mokmin, Mona Masood

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Guided by the theory of learning style, this study is based on the development of a multimedia learning application for students with mastery learning style. The learning material was developed by applying a graduated difficulty learning strategy. Algebraic fraction was chosen as the learning topic for this application. The effectiveness of this application in helping students learn is measured by giving a pre- and post-test. The result shows that students who learn using the learning material that matches their preferred learning style performs better than the students with a non-personalized learning material.

Keywords: algebraic fractions, graduated difficulty, mastery learning style, multimedia

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Authors: Waleed Afandi

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Artificial intelligence (AI) has rapidly transformed various sectors, including education. This paper explores the integration of AI in education, emphasizing its potential to revolutionize learning processes, enhance teaching methodologies, and personalize education. We examine the historical context of AI in education, current applications, and the potential challenges and ethical considerations associated with its implementation. By reviewing a wide range of literature, this study aims to provide a comprehensive understanding of how AI can be leveraged to improve educational outcomes and the future directions of AI-driven educational innovations. Additionally, the paper discusses the impact of AI on student engagement, teacher support, and administrative efficiency. Case studies highlighting successful AI applications in diverse educational settings are presented, showcasing the practical benefits and real-world implications. The analysis also addresses potential disparities in access to AI technologies and suggests strategies to ensure equitable implementation. Through a balanced examination of the promises and pitfalls of AI in education, this study seeks to inform educators, policymakers, and technologists about the optimal pathways for integrating AI to foster an inclusive, effective, and innovative educational environment.

Keywords: artificial intelligence, education, personalized learning, teaching methodologies, educational outcomes, AI applications, student engagement, teacher support, administrative efficiency, equity in education

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Authors: Amparo Camacho

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ABET accredited programs must assess the development of student learning outcomes (SOs) in engineering programs. Different institutions implement different strategies for this assessment, and they are usually designed “in house.” This paper presents a proposal for including standardized tests to complement the ABET assessment model in an engineering college made up of six distinct engineering programs. The engineering college formulated a model of quality assurance in education to be implemented throughout the six engineering programs to regularly assess and evaluate the achievement of SOs in each program offered. The model uses diverse techniques and sources of data to assess student performance and to implement actions of improvement based on the results of this assessment. The model is called “Assessment Process Model” and it includes SOs A through K, as defined by ABET. SOs can be divided into two categories: “hard skills” and “professional skills” (soft skills). The first includes abilities, such as: applying knowledge of mathematics, science, and engineering and designing and conducting experiments, as well as analyzing and interpreting data. The second category, “professional skills”, includes communicating effectively, and understanding professional and ethnical responsibility. Within the Assessment Process Model, various tools were used to assess SOs, related to both “hard” as well as “soft” skills. The assessment tools designed included: rubrics, surveys, questionnaires, and portfolios. In addition to these instruments, the Engineering College decided to use tools that systematically gather consistent quantitative data. For this reason, an in-house exam was designed and implemented, based on the curriculum of each program. Even though this exam was administered during various academic periods, it is not currently considered standardized. In 2017, the Engineering College included three standardized tests: one to assess mathematical and scientific reasoning and two more to assess reading and writing abilities. With these exams, the college hopes to obtain complementary information that can help better measure the development of both hard and soft skills of students in the different engineering programs. In the first semester of 2017, the three exams were given to three sample groups of students from the six different engineering programs. Students in the sample groups were either from the first, fifth, and tenth semester cohorts. At the time of submission of this paper, the engineering college has descriptive statistical data and is working with various statisticians to have a more in-depth and detailed analysis of the sample group of students’ achievement on the three exams. The overall objective of including standardized exams in the assessment model is to identify more precisely the least developed SOs in order to define and implement educational strategies necessary for students to achieve them in each engineering program.

Keywords: assessment, hard skills, soft skills, standardized tests

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Authors: Abdool Qaiyum Mohabuth

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Transferrable skills are learnt abilities which are mainly acquired when experiencing work. University students have the opportunities to develop the knowledge and aptitude at work when they undertake WBL placement during their studies. There is a range of transferrable skills which students may acquire at their placement settings. Several studies have tried to identify a core set of transferrable skills which students can acquire at their placement settings. However, the different lists proposed have often been criticised for being exhaustive and duplicative. In addition, assessing the achievement of students on practice learning based on the transferrable skills is regarded as being complex and tedious due to the variability of placement settings. No attempt has been made in investigating whether these skills are assessable at practice settings. This study seeks to define a set of generic transferrable skills that can be assessed during WBL practice. Quantitative technique was used involving the design of two questionnaires. One was administered to University of Mauritius students who have undertaken WBL practice and the other was slightly modified, destined to mentors who have supervised and assessed students at placement settings. To obtain a good representation of the student’s population, the sample considered was stratified over four Faculties. As for the mentors, probability sampling was considered. Findings revealed that transferrable skills may be subject to formal assessment at practice settings. Hypothesis tested indicate that there was no significant difference between students and mentors as regards to the application of transferrable skills for formal assessment. A list of core transferrable skills that are assessable at any practice settings has been defined after taking into account their degree of being generic, extent of acquisition at work settings and their consideration for formal assessment. Both students and mentors assert that these transferrable skills are accessible at work settings and require commitment and energy to be acquired successfully.

Keywords: knowledge, skills, assessment, placement, mentors

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Authors: Yirui Wang

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In the past few decades, patient safety has been the focus of much attention in the global medical and health field. As medical standards continue to improve and develop, the demand for patient safety is also growing. As one of the important dimensions in assessing patient safety, the Patient Perception Patient Safety Assessment Tool provides unique and valuable information from the patient's own perspective and plays an important role in promoting patient safety. This article aims to summarize and analyze the assessment content, assessment methods and applications of currently commonly used patient-perceived patient safety assessment tools at home and abroad, with a view to providing a reference for medical staff to select appropriate patient-perceived patient safety assessment tools.

Keywords: patients, patient safety, perception, assessment tools, review

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Authors: Ashwini Mahesh Jagatap

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This paper presents the language learning strategy with respect to speaking skill with collaborative learning approach. Collaborative learning has been proven to be efficient learning methodology for all kinds of students. Students are working in groups of two or more, reciprocally searching for understanding, Solutions, or meanings, or creating a product. The presentation highlights the different stages which can be implemented during actual implementation of the methodology in the class room teaching learning process.

Keywords: collaborative classroom, collaborative learning approach, language skills, traditional teaching

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Authors: Amani Alsaqqaf, Frederick W. B. Li

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Field trips are essential methods of learning in different subjects, and in recent times, there has been a reduction in the number of field trips (FTs) across all learning levels around the world. Virtual field trips (VFTs) in game environments provide FT experience based on the experiential learning theory (ELT). A conceptual framework for designing virtual field trip games (VFTGs) is developed with an aim to support game designers and educators to produce an effective FT experience where technology would enhance education. The conceptual framework quantifies ELT as an internal economy to link learning elements to game mechanics such as feedback loops which leads to facilitating VFTGs design and implementation. This study assesses the conceptual framework for designing VFTGs by investigating the possibility of applying immersive VFTGs in a secondary classroom and compare them with traditional learning that uses video clips and PowerPoint slides from the viewpoint of students’ perceived motivation, presence, and learning. The assessment is achieved by evaluating the learning performance and learner experience of a prototype VFT game, Island of Volcanoes. A quasi-experiment was conducted with 60 secondary school students. The findings of this study are that the VFTG enhanced learning performance to a better level than did the traditional way of learning, and in addition, it provided motivation and a general feeling of presence in the VFTG environment.

Keywords: conceptual framework, game-based learning, game design, virtual field trip game

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Authors: Tami Peterson

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Hyperbaric oxygen therapy (HBOT) has been hypothesized as an effective treatment for increasing verbal language skills in individuals on the autism spectrum. A child’s ability to effectively communicate with peers, parents, and caregivers impacts their level of independence and quality of personal relationships. This retrospective study will compare the speech development of participants aged 2-17 years that received 40 sessions of HBOT at 2.0 ATA to those who had not. Both groups will have a verbal assessment every six months. There were 31 subjects in the HBO group and 32 subjects in the non-HBO group. The statistical analysis will focus on whether hyperbaric oxygen therapy made a significant difference in Verbal Behavior Milestones Assessment and Placement Program (VB-MAPP) or Assessment of Basic Language and Learning Skills (ABLLS) results. The evidence demonstrates a strong correlation between HBOT and an increased change from baseline verbal scores compared to the control group, even in difficult to grasp areas such as spontaneous vocalization. We suggest this is due to the anti-inflammatory effects of hyperbaric oxygen therapy. Neuroinflammation causes hypoperfusion of critical central nervous system areas responsible for the symptoms described within the autism spectrum, such as problems with thought processing, memory, and speech. Decreasing the inflammation allows the brain to function properly, which results in improved verbal scores for the participants that underwent HBOT.

Keywords: assessment of basic language and learning skills, autism spectrum disorder, hyperbaric oxygen therapy, verbal behavior milestones assessment and placement program

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Authors: Marian Lissett Olaya

Abstract:

This article examined the factors associated with incorporating peer assessment into English language classes in a public university in Colombia. This is done in the context of writing English class for 4th-semester students. The research instruments consisted of peer assessment questionnaires, student diaries, and interviews. Findings showed that among the factors, motivation, frustration, anxiety, and lack of confidence appeared. Data revealed that peer assessment enables students to write competencies through training, teachers' guidance, and the provision of a collaborative environment.

Keywords: writing skills, peer assessment, formative assessment, language acquisition

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Authors: Darshana Lal, Sonu Rana

Abstract:

Learning Resource Centers (LRC) are acquiring different kinds of documents like books, journals, thesis, dissertations, standard, databases etc. in print and e-form. This article deals with the different types of sources available in LRC. It also discusses the concept of the web, as a tool, as a multimedia system and the different interfaces available on the web. The reasons for establishing LRC are highlighted along with the assignments of LRC. Different features of LRC‘S like self-learning and group learning are described. It also implements a group of activities like reading, learning, educational etc. The use of LRC by students and faculties are given and concluded with the benefits.

Keywords: internet, search engine, resource centre, opac, self-learning, group learning

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Authors: Shohreh Ghasemi

Abstract:

Introduction: Managing oral and maxillofacial trauma is a multifaceted challenge, as it can have life-threatening consequences and significant functional and aesthetic impact. Navigation techniques have been introduced to improve surgical precision to meet this challenge. A machine learning algorithm was also developed to support clinical decision-making regarding treating oral and maxillofacial trauma. Given these advances, this systematic meta-analysis aims to assess the efficacy of navigational techniques in treating oral and maxillofacial trauma and explore the impact of machine learning on their management. Methods: A detailed and comprehensive analysis of studies published between January 2010 and September 2021 was conducted through a systematic meta-analysis. This included performing a thorough search of Web of Science, Embase, and PubMed databases to identify studies evaluating the efficacy of navigational techniques and the impact of machine learning in managing oral and maxillofacial trauma. Studies that did not meet established entry criteria were excluded. In addition, the overall quality of studies included was evaluated using Cochrane risk of bias tool and the Newcastle-Ottawa scale. Results: Total of 12 studies, including 869 patients with oral and maxillofacial trauma, met the inclusion criteria. An analysis of studies revealed that navigation techniques effectively improve surgical accuracy and minimize the risk of complications. Additionally, machine learning algorithms have proven effective in predicting treatment outcomes and identifying patients at high risk for complications. Conclusion: The introduction of navigational technology has great potential to improve surgical precision in oral and maxillofacial trauma treatment. Furthermore, developing machine learning algorithms offers opportunities to improve clinical decision-making and patient outcomes. Still, further studies are necessary to corroborate these results and establish the optimal use of these technologies in managing oral and maxillofacial trauma

Keywords: trauma, machine learning, navigation, maxillofacial, management

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Authors: Bok Check Meng, Goh Ying Soon

Abstract:

Giving additional learning materials such as Chinese fantasy novel to non-native learners can be strenuous. Instructors have to understand the underpinning theories about cognitive theory for new word instruction. This paper discusses the underpinning theories. Relevant literature reviews are given. There are basically five major areas of cognitive related theories mentioned in this article. These include motivational learning theory, Affective theory of learning, Cognitive psychology theory, Vocabulary acquisition theory and Bloom’s cognitive levels theory. A theoretical framework has been constructed. Thus, this will give a hand in ensuring non-native learners might gain positive outcomes in the instruction process. Instructors who are interested in teaching new word from Chinese fantasy novel in specific to support additional learning might be able to get insights from this article.

Keywords: Chinese fantasy novel, new word teaching, non-native learners, cognitive theory, bloom

Procedia PDF Downloads 721