Learning Patterns Research Articles

Hypersensitivity of the nicotinic acetylcholine receptor subunit (CHRNA2L9′S/L9′S) in female adolescent mice produces deficits in nicotine-induced facilitation of hippocampal-dependent learning and memory

Adolescence is characterized by a critical period of maturation and growth, during which regions of the brain are vulnerable to long-lasting cognitive disturbances. Adolescent exposure to nicotine can lead to deleterious neurological and psychological outcomes. Moreover, the nicotinic acetylcholine receptor (nAChR) has been shown to play a functionally distinct role in the development of the adolescent brain. CHRNA2 encodes for the α2 subunit of nicotinic acetylcholine receptors associated with CA1 oriens lacunosum moleculare GABAergic interneurons and is associated with learning and memory. Previously, we found that adolescent male hypersensitive CHRNA2L9′S/L9′ mice had impairments in learning and memory during a pre-exposure-dependent contextual fear conditioning task that could be rescued by low-dose nicotine exposure. In this study, we assessed learning and memory in female adolescent hypersensitive CHRNA2L9′S/L9′ mice exposed to saline or a subthreshold dose of nicotine using a hippocampus-dependent task of pre-exposure-dependent contextual fear conditioning. We found that nicotine-treated wild-type female mice had significantly greater improvements in learning and memory than both saline-treated wild-type mice and nicotine-treated CHRNA2L9′S/L9′ female mice. Thus, hyperexcitability of CHRNA2 in female adolescent mice ablated the nicotine-mediated potentiation of learning and memory seen in wild-types. Our results indicate that nicotine exposure during adolescence mediates sexually dimorphic patterns of learning and memory, with wild-type female adolescents being more susceptible to the effects of sub-threshold nicotine exposure. To understand the mechanism underlying sexually dimorphic behavior between hyperexcitable CHRNA2 mice, it is critical that further research be conducted.

Low-Rank Tensor Regularized Views Recovery for Incomplete Multiview Clustering.

In real applications, it is often that the collected multiview data contain missing views. Most existing incomplete multiview clustering (IMVC) methods cannot fully utilize the underlying information of missing data or sufficiently explore the consistent and complementary characteristics. In this article, we propose a novel Low-rAnk Tensor regularized viEws Recovery (LATER) method for IMVC, which jointly reconstructs and utilizes the missing views and learns multilevel graphs for comprehensive similarity discovery in a unified model. The missing views are recovered from a common latent representation, and the recovered views conversely improve the learning of shared patterns. Based on the shared subspace representations and recovered complete multiview data, the multilevel graphs are learned by self-representation to fully exploit the consistent and complementary information among views. Besides, a tensor nuclear norm regularizer is introduced to pursue the global low-rank property and explore the interview correlations. An alternating direction minimization algorithm is presented to optimize the proposed model. Moreover, a new initialization method is proposed to promote the effectiveness of our method for latent representation learning and missing data recovery. Extensive experiments demonstrate that our method outperforms the state-of-the-art approaches.

Determination of early breeder in goldfish (Carassius auratus Linn.) with learning vector quantization, probabilistic and pattern recognition neural networks

It is common practice to categorize growing fish according to quality in fish farming centers. For such an application, experienced and estimating people are needed. By pre-selecting the right fish for the ornamental fish industry, it gets ahead of the competitors. This study deals with the classification of early breeder determination in goldfish using three different Artificial Neural Network (ANN) techniques. This classification model can help the fish industry assess classification risks and make the right decision. The used dataset was derived from the results of the classification section of 120 goldfish. It consisted of 7 input parameters (day, live weight, body length, head height, head width, body height, and current class). During trial, all goldfish fed by a diet contained 360 g crude protein and 4449.85 kcal metabolizable energy (kg / dry matter). The important types of classification ANNs, namely Learning Vector Quantization Neural Network (LVQNN), Probabilistic Neural Network (PNN), and Pattern Recognition Neural Network (PRNN) were employed for the machine learning scheme. The training and test performances of the ANN models were compared with the correct prediction ratio. They showed that all of the proposed ANN techniques were well at classification. However, the PRNN model was better than the LVQNN and PNN as a classifier for the breeder selection of goldfish. Therefore, the results of PRNN model such as histogram, Receiver Operating Characteristic (ROC) curve, regression, confusion matrix, accuracy, sensitivity, precision, and F1 score were given and discussed. Furthermore, the classification of early breeder determination in goldfish were examined for days with the best PRNN.

Artificial Intelligence in education: A comprehensive study

This comprehensive study delves into the multifaceted role of AI in education, exploring its applications, benefits, challenges, and future implications. The purpose of the study is to show how AI n education helps educators identify gaps in student knowledge and provide targeted feedback to improve learning outcomes. As a methodology, the library method and the study and review of various documents have been used in this research. The study examines the diverse range of AI technologies employed in educational settings, including intelligent tutoring systems, personalized learning platforms, educational chatbots, and virtual reality simulations. Furthermore, the study delves into the numerous benefits that AI brings to education. It highlights how AI-powered analytics and data-driven insights enable educators to gain deeper insights into student learning patterns, identify areas for improvement, and tailor instructional strategies accordingly. Additionally, AI-driven tools promote inclusivity by providing personalized support to learners with diverse needs and learning styles. Despite its transformative potential, the study also acknowledges the challenges and ethical considerations associated with integrating AI into education. Data privacy, algorithmic bias, and the digital divide are examined in detail, emphasizing the importance of responsible AI deployment and ethical guidelines. Looking ahead, the study explores the future implications of AI in education and the evolving role of educators in AI-enabled classrooms. It discusses how AI technologies will continue to evolve, offering new opportunities for collaborative learning, skill development, and lifelong education. In conclusion, this comprehensive study underscores the profound impact of AI on education and the need for thoughtful implementation strategies that prioritize equity, inclusivity, and ethical considerations. By harnessing the potential of AI, education systems can better prepare learners for the challenges and opportunities of the future.

Pedagogical Effects of CLIL in Asia’s Higher Education: An Empirical Reassessment

This research was a quasi-experiment that examined the effects of CLIL in an educational context in Taiwan’s higher education. Two groups of first-year undergraduate students were involved. One (65 students) was taught with CLIL; the other (59), the conventional approach. Their knowledge of the content and learning attitudes (self-efficacy and motivation) were quantitatively compared through achievement tests and a questionnaire. A qualitative semi-structured survey asked both groups for their perspectives on and perceptions of the treatments. The quantitative results show that both approaches were significantly effective for improving students’ knowledge of the content of the target subject (literary text), but the EG outperformed the CG. Likewise, both groups had positive learning attitudes to their treatments, but the EG also outweighed the CG. Furthermore, the qualitative accounts generated diverse results, reflecting the underlying difference between the approaches but showing that both approaches were welcomed. However, the conventional method was more favored than CLIL, mostly because of the participants’ learning preferences or because of the learning patterns which they had formed over years of studying in the specific cultural-education system (i.e., that of Taiwan) chosen for the study.

Deployment of Web-Based YOLO for CT Scan Kidney Stone Detection

This research aims to develop a kidney stone object detection system using machine learning techniques like YOLO and object detection, integrated into a Flask-based web interface to support early diagnosis by medical professionals. The trained model demonstrates strong pattern learning capabilities. Evaluation of the public dataset model reveals an average mean Average Precision (mAP) of 0.9698 for 'kidney stone' labels. This detection model exhibits high performance with an accuracy rate of 96.33%, precision of 96.98%, recall of 99.23%, and an F1-score of 98.1%. Clinical data evaluation shows that the YOLOv5-based detection system performs exceptionally well, with an average mAP of 0.9571, accuracy of 93.06%, precision of 95.71%, recall of 97.1%, and F1-score of 96.49%, indicating the model's capability to detect kidney stones with high precision and accuracy. Thus, both the evaluation on the public dataset and clinical dataset performance support accurate diagnosis processes and further treatment planning. Moreover, this research advances to the stage where the detection model can be directly utilized through implementation via Flask web deployment.

Pelatihan Penggunaan Media Pembelajaran Berbasis Permainan (Digital Game Bassed Learning) Menggunakan Aplikasi Kahoot bagi Guru Madrasah MIN 3 Langkat

Digital based game learning is a medium that contains educational content that is translated into games with the aim of involving students. Digital game based learning utilizes learning through learning patterns and playing using a computer or smartphone. Through this media, students are stimulated by three things at once, namely emotional intelligence, cognitive intelligence and psychomotor skills. This community service activity aims to improve the skills of participants, namely MIN 3 Langkat teachers, in using digital teaching media based on game learning. Implementation of community service is carried out through several stages such as Pre-Survey, Formation of a PKM Team, Making Proposals, Coordinating Teams and Partners, Preparing Training Tools & Materials, Implementing training, evaluating. The number of participants was around 25 MIN 3 Langkat teachers. They feel they have gained insights and skills that are applicable and useful. After attending the training, all participants who initially did not know and could not use the Kahoot application became aware and even 44% of the 25 participants were able to use the Kahoot application well.

DETECTING ANOMALIES IN VIDEOS USING MEMORY-AUGMENTED AUTOENCODER WITH KEY FRAME SELECTION

In this article, we propose a novel method to train a memory-augmented autoencoder in supervised mode by generating pseudo abnormal videos based on key frame selection techniques. Most video anomaly detection methods employ a machine learning model to learn patterns of normal videos. Any video where the patterns significantly deviate from the learnt patterns is considered an anomaly. However, developing an effective machine learning model for video anomaly detection is a challenging task due to the deficiency of anomalies. Specifically, abnormal samples are often much rarer and harder to collect than normal samples. To address this problem, we propose a novel approach using key frame selection techniques to generate pseudo anomalies. The generated pseudo anomalies are then combined with normal data to create the augmented dataset. The memory-augmented autoencoder is then trained on the augmented datasets. The experimental results show that the AUC scores of the proposed solution are higher than those of the base network architecture from 0.20% to 1.31% on three well-known datasets for video anomaly detection.

Penerapan Model Pembelajaran Kooperatif Tipe STAD dengan Pendekatan Open Ended untuk Meningkatkan Kemampuan Berpikir Kreatif Peserta Didik Berbantuan Video Interaktif pada Materi Fungsi Trigonometri Kelas XI SMA Negeri 1 Langke Rembong

This study is motivated by the lack of creative thinking skills of students in learning mathematics as well as one-way learning patterns from the teacher. The interview results confirmed that the creative thinking ability of students of SMA Negeri 1 Langke Rembong class XI MIPA is still relatively low. Therefore, the purpose of this study is to improve the creative thinking ability of students in class XI D SMA Negeri 1 Langke Rembong by applying the STAD type cooperative learning model and open-ended approach assisted by interactive video on trigonometric function material. The type of research used in this study is Classroom Action Research referring to the Kemmis & Mc Taggart model which is carried out in 2 cycles, where each cycle consists of 4 stages, namely: 1) Planning, 2) Implementation, 3) Observation, and 4) Reflection. The data collection techniques were observation, tests, and documentation while the data analysis was descriptive and qualitative. The results showed that the percentage of creative thinking ability of students in the innovative category of 7.14% in cycle 1 increased to 70.37% in cycle 2 of the 27 students' test results analyzed. The application of this learning approach and media learning model also increased the student activity score from 83.5 in cycle I to 100 in cycle II and the teacher activity score increased from 95 to 100 in cycle II. Thus, the application of the STAD-type cooperative learning model with an ended approach assisted by interactive video can improve the creative thinking ability of students of class XI D SMA Negeri 1 Langke Rembong on trigonometric function material.

Model Pengembangan Desain Instruksional Pada Materi Fluida Statik

The research carried out is related to assessing the use of learning models. The learning model used is the Instructional Design development model on Static Fluid material in Class XI SMA Negeri 1 Batangtoru. This model requires students to be more active in class. The use of this model will be combined with the use of modules as a learning resource, so that it can become an alternative for implementing learning. The aims of this research are 1) to describe learning using modules as an effective learning resource, 2) to describe student activities while using the Instructional Design Development Model in Static Fluid material in Class XI SMA Negeri 1 Batangtoru with modules as a learning resource, 3) to describe the results student learning while using the Instructional Design development model in Static Fluid material in Class Learning Resources.This research is action research which is developmental and pre-eliminary in nature, so it only uses one class. The research design uses Kemmis MC Taggart's cycle model with a One Group Pretest-Posttest Design learning pattern. This research was carried out at SMA Negeri 1 Batangtoru class XI MIPA1, with 34 students. This learning consists of three cycles. The implementation of learning in each cycle uses different syntax, so that you can find out which cycle is most effective. Student learning activities are divided into three stages, Instruction stage, Doing stage, and Evaluating stage. Student learning activities increase in each cycle. Student activities are in the active to very active category. The highest student activity is in cycle 3 with the very active category. Student scores increase from pretest to posttest in each cycle. The highest posttest average score was in cycle 2. The highest n-gain was also in cycle 2 with the medium category. Student learning retention is included in the very strong category. The most effective learning uses the Instructional Design development model in Static Fluid material in Class XI SMA Negeri 1 Batangtoru with modules as learning resources located in cycle 2. Based on the analysis of research data results, it can be concluded that the Instructional Design development model for Static Fluid material in Class XI SMA Negeri 1 Batangtoru with modules as learning resources is suitable for use in Static Fluid material in Class This model can be an alternative learning model implemented by teachers. This research requires thorough preparation, so that further research can be better prepared

Integrasi Sifat Mekanik dan Optik yang dimiliki Beton terhadap Pembelajaran Fisika dengan Penerapan Kurikulum Merdeka

The research carried out is related to assessing the use of learning models. The learning model used is the Instructional Design development model on Static Fluid material in Class XI SMA Negeri 1 Batangtoru. This model requires students to be more active in class. The use of this model will be combined with the use of modules as a learning resource, so that it can become an alternative for implementing learning. The aims of this research are 1) to describe learning using modules as an effective learning resource, 2) to describe student activities while using the Instructional Design Development Model in Static Fluid material in Class XI SMA Negeri 1 Batangtoru with modules as a learning resource, 3) to describe the results student learning while using the Instructional Design development model in Static Fluid material in Class Learning Resources.This research is action research which is developmental and pre-eliminary in nature, so it only uses one class. The research design uses Kemmis MC Taggart's cycle model with a One Group Pretest-Posttest Design learning pattern. This research was carried out at SMA Negeri 1 Batangtoru class XI MIPA1, with 34 students. This learning consists of three cycles. The implementation of learning in each cycle uses different syntax, so that you can find out which cycle is most effective. Student learning activities are divided into three stages, Instruction stage, Doing stage, and Evaluating stage. Student learning activities increase in each cycle. Student activities are in the active to very active category. The highest student activity is in cycle 3 with the very active category. Student scores increase from pretest to posttest in each cycle. The highest posttest average score was in cycle 2. The highest n-gain was also in cycle 2 with the medium category. Student learning retention is included in the very strong category. The most effective learning uses the Instructional Design development model in Static Fluid material in Class XI SMA Negeri 1 Batangtoru with modules as learning resources located in cycle 2. Based on the analysis of research data results, it can be concluded that the Instructional Design development model for Static Fluid material in Class XI SMA Negeri 1 Batangtoru with modules as learning resources is suitable for use in Static Fluid material in Class This model can be an alternative learning model implemented by teachers. This research requires thorough preparation, so that further research can be better prepared.

Signifikansi Model Blended Learning dalam Pembelajaran Pendidikan Agama Kristen di Lembaga Pendidikan

Learning activities should be carried out innovatively so that the material can be delivered well and students can understand it completely. Learning activities that are carried out innovatively can be implemented with a blended learning model, including Christian Religious Education learning which is able to collaborate offline and online learning approaches in schools as part of educational institutions. The aim of this research is to discuss the significance of the blended learning model in teaching Christian Religious Education in educational institutions. The method used is literature study by using scientific literature as a data collection tool. Any data that has been collected will be analyzed reductively through information filtering, organizing, and summarizing the discussion, so as to be able to explain the research results that the application of the blended learning model is very significant in the continuity of learning in educational institutions because it produces effective and efficient learning by combining face-to-face learning with online learning. The existence of the blended learning model is very significant because it helps students carry out Christian Religious Education learning activities in a fun way and increases students' enthusiasm and focus on learning in class. The blended learning pattern in the context of PAK learning which combines face to face and online learning can act as a forum for transferring and integrating religious values ??that support students' spiritual growth and form moral, ethical and social character in accordance with Biblical values.

Multi-level sequence denoising with cross-signal contrastive learning for sequential recommendation

Sequential recommender systems (SRSs) aim to suggest next item for a user based on her historical interaction sequences. Recently, many research efforts have been devoted to attenuate the influence of noisy items in sequences by either assigning them with lower attention weights or discarding them directly. The major limitation of these methods is that the former would still prone to overfit noisy items while the latter may overlook informative items. To the end, in this paper, we propose a novel model named Multi-level Sequence Denoising with Cross-signal Contrastive Learning (MSDCCL) for sequential recommendation. To be specific, we first introduce a target-aware user interest extractor to simultaneously capture users’ long and short term interest with the guidance of target items. Then, we develop a multi-level sequence denoising module to alleviate the impact of noisy items by employing both soft and hard signal denoising strategies. Additionally, we extend existing curriculum learning by simulating the learning pattern of human beings. It is worth noting that our proposed model can be seamlessly integrated with a majority of existing recommendation models and significantly boost their effectiveness. Experimental studies on five public datasets are conducted and the results demonstrate that the proposed MSDCCL is superior to the state-of-the-art baselines. The source code is publicly available at https://github.com/lalunex/MSDCCL/tree/main.

On Entropic Learning from Noisy Time Series in the Small Data Regime.

In this work, we present a novel methodology for performing the supervised classification of time-ordered noisy data; we call this methodology Entropic Sparse Probabilistic Approximation with Markov regularization (eSPA-Markov). It is an extension of entropic learning methodologies, allowing the simultaneous learning of segmentation patterns, entropy-optimal feature space discretizations, and Bayesian classification rules. We prove the conditions for the existence and uniqueness of the learning problem solution and propose a one-shot numerical learning algorithm that-in the leading order-scales linearly in dimension. We show how this technique can be used for the computationally scalable identification of persistent (metastable) regime affiliations and regime switches from high-dimensional non-stationary and noisy time series, i.e., when the size of the data statistics is small compared to their dimensionality and when the noise variance is larger than the variance in the signal. We demonstrate its performance on a set of toy learning problems, comparing eSPA-Markov to state-of-the-art techniques, including deep learning and random forests. We show how this technique can be used for the analysis of noisy time series from DNA and RNA Nanopore sequencing.

Timescales of learning in prefrontal cortex.

The lateral prefrontal cortex (PFC) in humans and other primates is critical for immediate, goal-directed behaviour and working memory, which are classically considered distinct from the cognitive and neural circuits that support long-term learning and memory. Over the past few years, a reconsideration of this textbook perspective has emerged, in that different timescales of memory-guided behaviour are in constant interaction during the pursuit of immediate goals. Here, we will first detail how neural activity related to the shortest timescales of goal-directed behaviour (which requires maintenance of current states and goals in working memory) is sculpted by long-term knowledge and learning - that is, how the past informs present behaviour. Then, we will outline how learning across different timescales (from seconds to years) drives plasticity in the primate lateral PFC, from single neuron firing rates to mesoscale neuroimaging activity patterns. Finally, we will review how, over days and months of learning, dense local and long-range connectivity patterns in PFC facilitate longer-lasting changes in population activity by changing synaptic weights and recruiting additional neural resources to inform future behaviour. Our Review sheds light on how the machinery of plasticity in PFC circuits facilitates the integration of learned experiences across time to best guide adaptive behaviour.

Multicultural Education in Developing Islamic Education Teaching Materials on Students' Tolerant Attitudes in Elementary Schools

This article aims to provide an overview of Multicultural Education in developing Islamic education Teaching Materials towards Students' Attitudes of Tolerance. The research method used is research in the form of a library study as a step in solving a problem by carefully and intensely reviewing relevant library data. The sources of library data in question are books, scientific articles and journals. The approach is descriptive qualitative, where the use of data is taken qualitatively and described or explained descriptively. Data processing to produce information is obtained through several processes including the process of searching for data, the process of collecting data, the process of processing/analyzing data, and the process of concluding data. The research results found that Islamic education learning through multicultural education ensures that students are not only able to understand and master the subject matter they study. In this case, what a teacher needs to do is form a Islamic education learning pattern through activities in the classroom; be universal and not discriminate between students; and inserting tolerance values in teaching materials.

Electrophysiological markers of orthographic pattern learning in school-aged children with reading challenges: An ERP investigation

BackgroundPrevious studies suggested that children with reading difficulty have impaired statistical learning ability in extracting distributional orthographic regularities. However, the neural mechanisms underlying have not been fully investigated. AimsThe current study aimed to identify the electrophysiological markers and to examine the neural underpinnings of statistical learning of orthographic regularities in children with reading difficulties. Methods and proceduresUsing the event-related potentials (ERPs) and the orthographic learning task, 157 children were exposed to a sequence of artificial pseudocharacters with varying levels of positional and semantic consistency (low at 60 %, moderate at 80 %, and high at 100 %). Outcomes and resultsPoor readers elicited an increased N170 response in the low consistency and a lack of left-lateralized P300 effect when learning positional regularities of radicals. Similarly, larger N170 effects were observed in poor readers, while similar N400 effects were found in both poor and average readers when learning semantic regularities of radicals. Conclusions and implicationsOur findings indicate that poor readers may have trouble using statistical information for early-stage orthographic pattern extraction, yet they can identify semantic inconsistencies after sufficient exposure. These results deepen our understanding of the neural mechanisms involved in statistical learning for poor readers and aid in improving criteria for differentiating between typically developing children and those with reading challenges.

Meningkatkan Keaktifan Siswa Kelas IX Pada Mata Pelajaran Fiqih Melalui Metode Resitasi di MTs Al Jam'iyatul Washliyah

Quality education is really needed by a nation to achieve the educational goals that have been set. Teachers as the main actors in the world of education really determine the quality of learning in schools. The reform era demands a Student Center Learning (SCL) learning pattern , where students are required to be more active and effective in participating in learning. Good quality teachers will be able to choose the right methods so that active student learning can be achieved. One of them is the application of the recitation method which is believed to increase students' active learning at school. The aim of this research is to increase students' active learning in Fiqh subjects in class IX. The method used in this research is classroom action research, by conducting two tests in cycle I and cycle II until satisfactory results. The data collection technique used in this research is observation technique. The results of this research are that the recitation method is proven to be able to increase students' active learning in the Fiqh class IX subject at MTS Al Jam'iyatul Washliyah Completed by 26.19%. From 69.64% in cycle I to 95.83% in cycle II.

College English Mobile Learning Patterns Based on Multi-Modal Learning From “Internet +” Perspective

Under the background of Internet Plus, the rapid development of the mobile Internet technology has led to the widespread use of the PCs and smartphones, bringing out new chances for college English mobile learning. More importantly, with the trend of globalization, the complex situation has set higher demands for this generation. In order to promote college students’ English learning effectiveness and enhance comprehensive English skills, this paper explores possible mobile learning patterns based on multi-modal learning that college students can apply in English learning, according to the theories of the Multi-modal Discourse Analysis and mobile learning. Included in the study are the employment of questionnaires and interviews. The results show that teachers’ construction of multi-modal teaching and students’ after-class multi-modal learning play a significant role in improving college students’ English proficiency. The research, therefore, will provide some possible insight into cultivating college students’ comprehensive English skills to adapt to the changing society.

Implementation of Critical Literacy Learning in Primary Education Through a Simple Research Writing Project

Critical literacy skills are important for students to master. Literate students are students who have critical awareness of themselves and their environment so that they are able to critically and objectively solve problems. To form this mental attitude, the implementation of critical literacy learning needs to be constructed properly. Critical literacy learning is centered on texts and responses to texts that are realized through listening, reading, speaking, and writing tasks that are carried out in a balanced manner in a challenging task frame for students. Writing a research report requires objective analysis of the text and contextual problems found in the field, therefore research learning is one form of critical literacy learning. This research method is a qualitative method with an exploratory research type. This study aims to describe the implementation of critical literacy learning in elementary education. Data collection uses documentation, interview and observation techniques with the main instrument being the researcher himself. In collecting data on critical literacy learning planning, the researcher was assisted by additional instruments, the researcher used observation sheets, and semi-structured interview sheets with teachers and students. To ensure the validity of the data, triangulation of sources and methods was used. The results of the study show that the implementation pattern of learning constructed in critical literacy learning is to expose students to various readings to construct theories with meaningful experiences, understand readings by reviewing them from various perspectives, find contextual problems, and discuss contextual problems based on theory and objectivity. The assessment carried out by the teacher is an assessment that uses various forms with representative instruments. In addition, student involvement in the assessment will determine objectivity. Of the 5 criteria proposed to measure critical literacy skills, students have only reached the third stage, namely analytical. This happens because the learning process carried out by the teacher has not met the requirements of good feedback strategies, representative assignments and maximum facilitation from the teacher.