Learning Assessment System Research Articles

ASSESSMENT SYSTEM FOR ARABIC LANGUAGE LEARNING WITHIN THE INDEPENDENT CURRICULUM

The Arabic Language Learning Assessment System explores a range of evaluative approaches aimed at measuring student progress in Arabic language acquisition. This study delves into various assessment methods and strategies for evaluating communicative competencies, reading, writing, and other linguistic skills pertinent to Arabic. It also highlights the significance of adopting diverse and contextually appropriate assessment techniques. Moreover, the study discusses how an effective assessment framework can enhance students' comprehension and proficiency in Arabic. Findings indicate that the Independent Learning Curriculum significantly contributes to the educational process, with an emphasis on student engagement through both summative and formative assessments. It is recommended that educational institutions innovate by improving learning facilities, particularly through enhanced technological support, such as the integration of projectors in the learning environment. This study underscores the necessity for continuous development in educational tools and strategies to better support Arabic language learning.

Modeling and Reinforcement Learning Assessment System for Quality Improvement of Advertising Design

Modeling and Reinforcement Learning Assessment System for Quality Improvement of Advertising Design

Research on the Application of PBL + SPOC Blended Teaching Model in Probability and Statistics Course

To cultivate talents with an exploratory spirit and practical skills in the era of information technology, it is imperative to reform teaching methods and approaches. In the teaching process of the Probability and Statistics course, an application-oriented blended teaching model combining problem-based learning and small private online course was explored. By organizing and implementing online and offline teaching activities based on problem-based learning, a multidimensional process-oriented learning assessment system was established. Practice has shown that this model can effectively enhance classroom teaching effectiveness, benefiting the improvement of students’ overall skills and mathematical literacy.

Learning strategy regulation processes with rubrics for learning assessment

Learning assessment can be done with the help of the development of rubrics. Rubrics are used to evaluate a wide variety of aspects of the pedagogical process; they are even very efficient for standardizing assessment and creating feedback. The adoption of rubrics helps establish educationally appropriate criteria and performance levels for both metrics and performance measurements, including complex learning structures such as the pedagogical framework. Regulated learning frameworks has come to be cornerstone for examining learning forms of regulation. Despite recent advances in the area of self-regulated and co-regulation, more research is still needed on how groups of students regulate their learning in learning environments in the classroom context. In this work we apply, we re-designed Pintrich’s self-regulation framework, placing a special emphasis on the crucial role of performance measurement in learning with the aid of rubrics, providing a more holistic view of regulatory processes. The extended framework presented here has implications for practice, being especially beneficial in creating strategies for facilitating students’ self-regulation and co-regulation. This study provides valuable information for educators regarding instructional design and the selection of appropriate regulatory processes to shape and measure learning activities within a framework. It was developed a complete prototype called the Learning Assessment System by Rubrics.

The Journey towards English Syllabi Unification.

The aim of this paper is to describe the process undertaken by Curriculum Coordinators to design and update English syllabi across all Language Institutes at Universidad Santo Tomás (USTA) in Colombia. It outlines the foundational reasons for updating university syllabi to establish a cohesive set of five English syllabi corresponding to the undergraduate programs’ five English levels at USTA. These programs align with the Learning Assessment System (SEA in Spanish), the University Pedagogical Model, and international standards aimed at fostering communicative and intercultural competences in English as a Foreign Language (EFL). This academic endeavor was grounded in the principles of action research and involved gathering data from institutional documents, as well as surveying the perceptions of directors and curriculum coordinators regarding the English syllabi. The process also incorporated collaborative work as a strategy to consolidate a common framework for English syllabi at USTA. Thus, the design and updating of English syllabi has allowed all the university headquarters and branches to set a common guiding ground for English teaching and learning processes. This initiative has also contributed to the standardization of competences, learning goals, contents, didactic activities, times, outcomes, and assessment for each academic term within the five English levels offered.

English Speaking Assessment Algorithm Based on Deep Learning

English as a Foreign Language (EFL) students perform when speaking in public. An increasingly globalized world, effective public speaking is critical, but EFL students struggle to perform it, despite importance of qualities such as eye contact, speech pauses, there is presently no objective examination of such elements. A summative assessment has historically been the predominant form of evaluation in college English speaking assessments. Exam-centric teaching has considerable negative effect on foreign language training. In this research work, English Speaking Assessment Algorithm Based on Deep Learning (ESA-NEGCN-NBOA) is proposed. Initially, input video data are gathered from the multiple video dataset (MVD).The input video data is then pre-processed using Deep Attentional Guided Image Filtering (DAGIF) to remove presence of signal-dependent noise and improve lack of pixels from the regions and enhanced the video data. The data that has been pre-processed is utilized to Feature extraction using New General Double Integral Transform (NGDIT), which extract the significant attributes such as mel-frequency cepstral coefficients, energy, speech rate and pitch. Then NEGCN is proposed to improve students spoken English performance by assessmenting the English speakers. In general, NEGCN doesn’t express some adaption of optimization approaches for determining optimal parameters to promise exact improvement of assessment. Therefore, NBOA is proposed to enhance weight parameter of NEGCN for English speaking assessments, which precisely assess the English speaking. Performance measures such as accuracy, assessment error, evaluation time, pretest and posttest are examined when the proposed ESA-NEGCN-NBOA method is put into practice. The proposed ESA-NEGCN-NBOA method attains21.36%, 23.42% and 19.29% higher accuracy, 23.36%, 18.42% and 28.27% lower evaluation error, 20.36%, 27.42%, 28.17% lesser evaluation time analysed with existing techniques, likes innovative strategy towards oral English assessment utilizing machine learning, data mining, blockchain methods(IST-OEA-ML), machine learning assessment system for spoken English depend on linear predictive coding (AS-SE-LPC-ML), multimodal transfer learning for oral presentation assessment (MM-TL-OPA) respectively.

Evaluation of the learning state of online video courses based on functional near infrared spectroscopy.

Studying brain activity during online learning will help to improve research on brain function based on real online learning situations, and will also promote the scientific evaluation of online education. Existing research focuses on enhancing learning effects and evaluating the learning process associated with online learning from an attentional perspective. We aimed to comparatively analyze the differences in prefrontal cortex (PFC) activity during resting, studying, and question-answering states in online learning and to establish a classification model of the learning state that would be useful for the evaluation of online learning. Nineteen university students performed experiments using functional near-infrared spectroscopy (fNIRS) to monitor the prefrontal lobes. The resting time at the start of the experiment was the resting state, watching 13 videos was the learning state, and answering questions after the video was the answering state. Differences in student activity between these three states were analyzed using a general linear model, 1s fNIRS data clips, and features, including averages from the three states, were classified using machine learning classification models such as support vector machines and k-nearest neighbor. The results show that the resting state is more active than learning in the dorsolateral prefrontal cortex, while answering questions is the most active of the three states in the entire PFC, and k-nearest neighbor achieves 98.5% classification accuracy for 1s fNIRS data. The results clarify the differences in PFC activity between resting, learning, and question-answering states in online learning scenarios and support the feasibility of developing an online learning assessment system using fNIRS and machine learning techniques.

Implementing Applications for Formative Assessment to Enhance Teacher Competence in Learning Assessment

Abstract: Implementing formative assessment applications in learning assessment within the Merdeka curriculum can increase teacher proficiency in administering assessments. This study examines the impact of formative assessment applications on teacher competency in Merdeka curriculum learning assessment. This study employed an experimental design with 20 instructors from SMA Muhammadiyah 6 Yogyakarta, separated into experimental and control groups. The experimental group utilized formative assessment applications, whereas the control group relied on conventional assessment techniques. The results indicated that the use of formative assessment applications could substantially improve (p 0.05) teacher competence in Merdeka curriculum learning assessment. The experimental group's post-test mean was higher than the control group's. In addition, instructors consider using formative assessment more effective and efficient. This finding has significant implications for the future development of the Merdeka curriculum learning assessment system.

Exploring the blended learning model of music teaching skills for teacher trainees based on teacher training professional certification in the context of big data

Abstract The existing teaching model has the problems of a single learning mode and students’ interest in learning, so it is necessary to build a blended learning model scenario to promote students’ interest in learning. This paper proposes an educational data mining algorithm for the blended learning model of music teaching skills in the context of big data and proposes a blended learning model of teaching skills based on the PSO algorithm. Since the PSO particle swarm algorithm has the problem of low accuracy and overfitting, the XGBoost algorithm model is introduced based on the PSO particle swarm algorithm, and the Iris dataset is clustered. For the evaluation analysis of the blended learning model of music skills, 13 indicators were observed for three randomly selected students in this study. The accuracy of the optimized PSO-XGBoost algorithm was 0.95, which was 10% more accurate than the pre-optimized algorithm, and the overall accuracy was significantly improved. The three students scored 18.96, 18.97, and 19.61 in the music skills blended learning model evaluation learning assessment system evaluation, with the highest score reaching 19.61. The study showed that the music-teaching blended learning model is comprehensive and easy to implement in accordance with the existing teaching environment.

THE INFLUENCE OF CURRICULUM AND ASSESSMENT POLICIES AND PRACTICES ON STUDENT ENGAGEMENT AND DROPOUT RISK IN SECONDARY EDUCATION IN MOGADISHU, SOMALIA

The purpose of this research was to investigate the influence of curriculum and assessment policies and practices on student engagement and dropout risk in secondary schools in Mogadishu, Somalia. To combine the data from diverse sources, the research employed a literature review strategy. Dropout risk was defined as the possibility of students leaving school before finishing their secondary education, while student engagement was described as the degree of participation, interest, and excitement that students display in their learning process. Motivation, expectations, mental health, substance abuse, parental involvement, grade retention, IQ, learning difficulties, academic achievement, curriculum quality, relevance, consistency, alignment, teacher capacity, teaching materials, assessment system, governance, and management were identified as factors influencing student engagement and dropout risk at the individual, classroom, school, and system levels. The study found that the curriculum and assessment policies and practices in Mogadishu-Somalia were low in quality, inconsistent, irrelevant, and misaligned with the national standards and the needs of the learners and society. The study recommended improving and aligning the curriculum and assessment policies and practices in secondary education in Mogadishu-Somalia with the national standards, the needs of the learners and society, and the principles of student engagement and differentiation. To achieve this goal, the study suggested developing and sharing a clear vision and goals, involving all stakeholders in the curriculum and assessment processes, adapting the curriculum and assessment to the diverse needs of students, engaging and motivating students in the curriculum and assessment, and improving teacher capacity, curriculum framework, teaching and learning materials, assessment and certification system, and governance and management of the education sector.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0075/a.php" alt="Hit counter" /></p>

Workshop Asesmen Nasional bagi Guru-Guru Sekolah Dasar Binaan Astra di Takari, Nusa Tenggara Timur

The challenges of 21st-century learning lead the Indonesian government to make innovations in the education world, one of which is in the learning assessment system. The policy of abolishing the UN and USBN and then proceeding with the implementation of the National Assessment has been carried out since 2020. This is a good policy but teachers and principals' understanding of an assessment system like this still requires assistance. For this reason, this Community Service (PkM) activity was carried out. The PkM team from the Mathematics Education Study Program, Nusa Cendana University collaborated with the Astra Education Foundation – Michael D. Ruslim (YPA-MDR) and four Astra-assisted elementary schools in Takari, NTT, so that there were four principals and thirty-nine teachers who were actively involved in this activity. The Lecture method, question-and-answer, practices, and demonstrations were the methods used. This activity was carried out for three days and went through several stages: preparation, implementation, evaluation-reflection. The results show that this PkM activity has succeeded in achieving the set goals: 1) participants are able to develop Literacy and Numeracy tasks, 2) understand what school activities can be developed as part of implementing the Pancasila student profile and based on nine aspects of the Learning Environment Survey.

Bloom’s Taxonomy and Examination Reform in Higher Education using ICT as a Tool

This study highlights the basic features of Bloom’s Taxonomy and its importance in integrated teaching- learning-assessment system. This study detailed a plan of information and Communications Technology (ICT) based implementation of revised Bloom’s taxonomy (2001) as a mark of examination reform to analyze students’ attainment level by measuring knowledge level (K), course outcome (CO) and program outcome (PO) in respect to each curriculum. The plan ultimately facilitate to develop a portal and fulfil the basic objective of Outcome based Education (OBE) system as the students’ attainment report is one of the required field for accreditation by National Assessment and Accreditation Council (NAAC).

The Effects of Using Virtual Reality on Thai Word Order Learning

Thai has its own unique spelling system and grammatical rules. Its word order is quite different from that of Mandarin and English, thus making it more difficult for students in Taiwan to learn. Past studies also point out that learning word order is one of the most difficult aspects when learning foreign languages. As science and technology advance, emerging technologies have been widely applied in foreign language learning. This research aims to explore the effect of using a multi-language VR learning assessment system on assisting Thai learners to learn grammatical word order, and to investigate the correlates between Thai self-efficacy, Thai language anxiety, word order learning retention, and task value of VR learning. In order to accomplish this purpose, we invited Thai learners who took Thai courses in the continuing education division of a national university in northern Taiwan to participate in a 5-week teaching experiment, during which the participants were asked to practice Thai word order for 20 min. They were administered a questionnaire to fill out after five weeks of practice and were tested for retention one month after the experiment. A total of 84 valid questionnaires were collected, with an effective return rate of 93.3%. Of the respondents, 30 were male (35.7%), and 54 were female (64.3%). The data were subjected to item analysis, reliability and validity analysis, and then underwent PLS-SEM for research model validation. The results revealed that: (1) Thai language self-efficacy was positively related to learning retention and task value; (2) Thai language anxiety was negatively related to learning retention and task value; (3) Learning retention was positively related to the task value of learning and continuous usage intention.

Management of Initial Assessment Implementation in Independent Early Childhood Education Curriculum

One of the characteristics of implementing an independent curriculum is student-centered learning. The term in the independent curriculum is closely related to the philosophy of Education Ki Hajar Dewantara, namely the curriculum that servitudes children. This philosophy starts from the learning objectives, planning, implementation, and assessment system as well as the evaluation of Learning in the Early Childhood Education environment is the responsibility of the teacher for the results of activities achieved by students. The teacher is tasked with measuring whether students have achieved proper development from 5 (five) aspects of basic skills, including religious and moral, cognitive, social-emotional, language, and physical motor also child growth, including weight, height, head circumference, and upper arm circumference. The initial assessment aims to uncover and recognize the characteristics of learners, identifying learners' competencies, strengths, and weaknesses. The results are used by educators as a reference to plan a learning process according to learning needs. This research shows that the initial management of 'School Mover' and 'Non-School Mover' requires management in its implementation and it is integrated part of the learning process in realizing the Pancasila Student Profiles.

English Language at Secondary Level in Bangladesh: (Dis)connections Between Policy and Practice of Oral Skills

The development of curriculum, textbooks and assessment is a continuous process for better teaching and learning outcomes. The National Curriculum & Textbook Board (NCTB) revised its secondary curriculum in 2012 for English education considering the 2010 National Education policy. The only textbook for the whole country for secondary level, English for Today has been developed accordingly in 2013 for grades 6 to 10, to help students attain competency in listening, speaking, reading, and writing. This qualitative study is based on semi-structured interviews and content analysis of pertinent policy documents. The semi-structured interview data includes a set of English curriculum policy implementation stakeholders including teacher trainers, school principals and English teachers. This paper aims to explore the reasons for the existing disconnections coherently through the analytical lens of the Constructive Alignment (CA) Model for curriculum design to achieve the intended learning outcomes for secondary English education in Bangladesh. The findings support the argument that if the coherence of secondary curriculum, classroom teaching and learning activities and assessment system is not aligned, the aspirations of the National Education Policy 2010 may not be achieved.

Analyzing the Impact of Artificial Intelligence in Personalized Learning and Adaptive Assessment in Higher Education

This This research aims to examine the impact of AI on personalized learning and adaptive assessment in higher education and investigate the ethical and social implications of using AI in these contexts. A mixed-methods approach was used, involving surveys, interviews, focus groups, institutional records, and system logs to collect both quantitative and qualitative data. The population included higher education institutions that use AI in personalized learning and adaptive assessment systems, as well as students and educators who use these systems. The results of the study showed that AI-based systems had a positive impact on student engagement and motivation, as well as providing personalized learning experiences. However, the analysis also revealed some limitations and potential concerns, such as technical issues and the potential for bias in the AI algorithms used in these systems. Ethical and social implications were analyzed using ethical frameworks such as the Belmont Report and principles of distributive justice. To ensure ethical and socially responsible use of AI in personalized learning and adaptive assessment, clear guidelines and standards for the development and implementation of these systems need to be established. This includes promoting transparency and accountability in the use of student data, ensuring that algorithms are developed and validated in a fair and unbiased manner, and involving diverse stakeholders in the design and implementation of these systems to promote equity and fairness. Informed consent should also be obtained from students and other stakeholders, and measures should be taken to ensure that student data is kept confidential and secure. Ongoing monitoring and evaluation should be conducted to assess the impact of AI-based systems on student outcomes and to identify and address any unintended consequences or biases.

A Machine Learning Assessment System for Spoken English Based on Linear Predictive Coding

In the teaching of English, there is an increasing focus on practical communication skills. As a result, the speaking test component has received more and more attention from education experts. With the rapid development of modern computer technology and network technology, the use of computers to assess the quality of spoken English has become a hot topic of research in related fields at present. A machine learning assessment system based on linear predictive coding is proposed in order to achieve automatic scoring of spoken English tests. First, the principle of linear predictive coding and decoding is analyzed, and the traditional linear predictive coding and decoding algorithm is improved by using hybrid excitation instead of the traditional binary excitation. Second, the overall structure of the machine learning assessment system is designed, which mainly includes division into four modules: acoustic model acquisition module, speech recognition module, standard pronunciation transcription module, and decision module. Then, the speech recognition module is implemented by an improved linear predictive speech coding method to acquire the feature parameters of the speech signal and generate the speech feature vector. Finally, the convolutional neural network algorithm is used to train the speech features so as to implement the acoustic model acquisition module. The experimental results show that the improved linear predictive speech coding method yields more natural and higher intelligibility speech signals. The designed machine learning evaluation system is able to accurately detect information about the quality of the learner’s pronunciation.

HONG KONG AND NEW ZEALAND LEARNING ASSESSMENT SYSTEM (Literature Study and Inspiration for Learning Assessment of Islamic Religious Education in Indonesia)

The learning assessment process is still an interesting discussion theme, especially with the presence of the term AfL (Assessment for Learning) which is a development of the AoL (Assessment of Learning) concept. The purpose of this article is to describe the implementation of AfL in two different regions, Hong Kong and New Zealand with the indication that there are several studies showing that AfL is running well in these two regions. The results of the description are then linked to the context of the assessment of Islamic Religious Education learning in Indonesia today. This research is a literature study with a qualitative model that begins with the search for sources (heuristics), assessment (criticism) and construction. As a result, Hong Kong presents an assessment system in the form of BCA (Basic Competency Assessment) and SBA (School-Based Assessment); while New Zealand implemented several policies to strengthen the implementation of this AfL. When referring to the implementation of AfL in the two regions, Indonesian Islamic Education requires teachers who are prepared and competent in carrying out the assessment. The Islamic Religious Education assessment system is very detailed and clear, but teachers are still not able to apply it.

Students’ mathematical literacy skills in solving higher-order thinking skills problems

Higher-order thinking (HOTS) problems are a learning assessment system applied to the curriculum in 2013 to improve students' higher-level thinking skills. However, teachers still familiarize students to solve problems with low-level thinking, which lower the Indonesian students’ mathematical literacy. This descriptive research with a qualitative approach aimed to explore junior high school students’ mathematical literacy skills in Kotapinang in solving HOTS problems applied to the curriculum 2013. Four students were selected as research subjects. Research instruments consisted of mathematical skills tests, literacy tests, and interviews. The researchers applied the triangulation techniques with Miles and Huberman’s model as the data analysis technique. The analysis showed that students’ mathematical literacy skills in Kotapinang were poor. The researchers recommend applying technology-based learning models, such as blended learning that is suitable for limited face-to-face learning to support the improvement of mathematics literacy skills of junior high school students in solving HOTS problems in the curriculum 2013.

Efektivitas Penilaian Pembelajaran Menggunakan Google Form pada Pembelajaran Daring

Learning in the network implemented in pandemic covid-19 is a new challenge for the Indonesian learning system. The demands of more creativity are left to the educators for effective learning. So, too, with new options/ideas associated with the learning system, especially with the student learning assessment system. The feature of the Google form on the Google application becomes one of the options that can be used to facilitate the student learning assessment process. The study is conducted to learn the effectiveness of learning assessments using Google form on students, the strengths and deficiencies of Google form, and the knowledge of barriers students experience when using Google form. Research is conducted with a descriptive qualitative method with the data-collection of interviews and questionnaires. The results of the study say that the use of the learning assessment using Google form is considered to be effective because it makes it easier for teachers and students, both in filling out problems and process processes by teachers. Google form has an advantage such as providing an automated data-processing system, so teachers don't have to manually calculate. The barriers are affected by network activity, and the lack of understanding of students or guardians of technology.