Alternative Learning Strategies Research Articles

Higher-Order Thinking Skills HOTS-based literacy media: An innovative learning strategy to promote the secondary students' social awareness

In this high-technology era, students are increasingly inclined to use digital services such as Facebook, Instagram, and YouTube. Unsurprisingly, most of them are becoming more addicted to using their digital devices. Unfortunately, the accessed contents are not always suitable and reliable for their needs and ages. Therefore, they absorb all information directly without filtering the messages. This study scrutinizes the implementation of Higher-Order Thinking Skills (HOTS)-based media literacy to promote the critical social awareness of junior high school students in an EFL classroom. A case study was employed as a research design involving one eighth-grader class and one EFL teacher as participants. The data were gathered via classroom observations, interviews with the teacher and the students, and document analysis. The data were then analyzed qualitatively by referring to the principles of teaching media literacy, Higher-Order Thinking Skills, and social awareness. The findings of this study revealed that the teacher applied some principles in teaching media literacy, namely introducing general concepts, making generalizations, analyzing information, evaluating the content of information, and drawing a conclusion from the students' actions. These principles consequently promoted the students' critical social awareness, including emotional awareness, self-regulation, empathy, active listening, cooperation, and respect. Considering such benefits, HOTS-based media literacy can be used as an alternative learning strategy to promote the students' critical social awareness in EFL classrooms.

Cognitive effort detection for tele-robotic surgery via personalized pupil response modeling.

Gaze tracking and pupillometry are established proxies for cognitive load, giving insights into a user's mental effort. In tele-robotic surgery, knowing a user's cognitive load can inspire novel human-machine interaction designs, fostering contextual surgical assistance systems and personalized training programs. While pupillometry-based methods for estimating cognitive effort have been proposed, their application in surgery is limited by the pupil's sensitivity to brightness changes, which can mask pupil's response to cognitive load. Thus, methods considering pupil and brightness conditions are essential for detecting cognitive effort in unconstrained scenarios. To contend with this challenge, we introduce a personalized pupil response model integrating pupil and brightness-based features. Discrepancies between predicted and measured pupil diameter indicate dilations due to non-brightness-related sources, i.e., cognitive effort. Combined with gaze entropy, it can detect cognitive load using a random forest classifier. To test our model, we perform a user study with the da Vinci Research Kit, where 17 users perform pick-and-place tasks in addition to auditory tasks known to generate cognitive effort responses. We compare our method to two baselines (BCPD and CPD), demonstrating favorable performance in varying brightness conditions. Our method achieves an average true positive rate of 0.78, outperforming the baselines (0.57 and 0.64). We present a personalized brightness-aware model for cognitive effort detection able to operate under unconstrained brightness conditions, comparing favorably to competing approaches, contributing to the advancement of cognitive effort detection in tele-robotic surgery. Future work will consider alternative learning strategies, handling the difficult positive-unlabeled scenario in user studies, where only some positive and no negative events are reliably known.

Hippocampal lesions impair non-navigational spatial memory in macaques.

Decades of studies robustly support a critical role for the hippocampus in spatial memory across a wide range of species. Hippocampal damage produces clear and consistent deficits in allocentric spatial memory that requires navigating through space in rodents, non-human primates, and humans. By contrast, damage to the hippocampus spares performance in most non-navigational spatial memory tasks-which can typically be resolved using egocentric cues. We previously found that transient inactivation of the hippocampus impairs performance in the Hamilton Search Task (HST), a self-ordered non-navigational spatial search task. A key question, however, still needs to be addressed. Acute, reversible inactivation of the hippocampus may have resulted in an impairment in the HST because this approach does not allow for neuroplastic compensation, may prevent the development of an alternative learning strategy, and/or may produce network-based effects that disrupt performance. We compared learning and performance on the HST in male rhesus macaques (six unoperated control animals and six animals that underwent excitotoxic lesions of the hippocampus). We found a significant impairment in animals with hippocampal lesions. While control animals improved in performance over the course of 45 days of training, performance in animals with hippocampal lesions remained at chance levels. The HST thus represents a sensitive assay for probing the integrity of the hippocampus in non-human primates. These data provide evidence demonstrating that the hippocampus is critical for this type of non-navigational spatial memory, and help to reconcile the many null findings previously reported.

The Role of the Cerebellum in Learning to Predict Reward: Evidence from Cerebellar Ataxia.

Recent findings in animals have challenged the traditional view of the cerebellum solely as the site of motor control, suggesting that the cerebellum may also be important for learning to predict reward from trial-and-error feedback. Yet, evidence for the role of the cerebellum in reward learning in humans is lacking. Moreover, open questions remain about which specific aspects of reward learning the cerebellum may contribute to. Here we address this gap through an investigation of multiple forms of reward learning in individuals with cerebellum dysfunction, represented by cerebellar ataxia cases. Nineteen participants with cerebellar ataxia and 57 age- and sex-matched healthy controls completed two separate tasks that required learning about reward contingencies from trial-and-error. To probe the selectivity of reward learning processes, the tasks differed in their underlying structure: while one task measured incremental reward learning ability alone, the other allowed participants to use an alternative learning strategy based on episodic memory alongside incremental reward learning. We found that individuals with cerebellar ataxia were profoundly impaired at reward learning from trial-and-error feedback on both tasks, but retained the ability to learn to predict reward based on episodic memory. These findings provide evidence from humans for a specific and necessary role for the cerebellum in incremental learning of reward associations based on reinforcement. More broadly, the findings suggest that alongside its role in motor learning, the cerebellum likely operates in concert with the basal ganglia to support reinforcement learning from reward.

Mnemonic techniques in medicine: experience of dental mnemonics usage in teaching of therapeutic dentistry for foreign students

Annotation. The ability to memorize new and vast material is a necessary component of students’ success. Mnemonic techniques are a variety of strategies that help to store complex and extensive information in long-term memory. Most researchers consider that mnemonics improve memory by using natural memory processes such as visual imagery, organization, and detailed encoding. Mnemonic techniques can lead to long-term storage of information and can work with complex materials in combination with other techniques when the appropriate conditions are created. The purpose of the study was the implementation of dental mnemonics when teaching of therapeutic dentistry for foreign students to facilitate memorization, reproduction and analysis of vast amounts of information. A review of the literature was performed and the results were synthesized in the form of a narrative. The manuscript presents dental mnemonics and mnemonic techniques, which are used in integration with other teaching methods for English-speaking students to facilitate mastering of the material in order to improve their knowledge, skills and abilities. We used verbal, visual and linguistic dental mnemonics. It was established that foreign students prefer alternative learning strategies, among various mnemonic techniques choose the simple methods. The most widely used mnemonic among students is the technique of first letters (or acronyms), followed by rhyming and keyword methods. Complex techniques such as the methods of loci, binding and phonetic system are the least popular. Mnemonics facilitate learning, consolidation and recall of information, that significantly improves training productivity. Mnemonic techniques cannot replace standard teaching methods, but in conjunction with other strategies, it is an effective educational tool. In the future, new mnemonics will be developed to present fresh information in a more systematic and organized format, which can be used as a step for creation updated mnemonic technique.

Does student's critical thinking and collaboration skills can empower through investigation and thinking learning strategy?

The low critical thinking skills and collaboration skills of students in biology learning are caused by the dominance of conventional learning, so they require alternative learning strategies. This study aims to determine the effect of GITTW learning strategy on student critical thinking and collaboration skills. The research design used was quasi-experiment with a pre-test and post-test control group design. The class X of Science-2 and of Science-3 SMA Negeri 01 Paciran became sample (N=72), with details; the control class and treatment class consisting of 36 students. Data collection critical thinking skills using easy test before and after treatment with Facione rubric developed and data collaborative skills using observation sheet assessment rubric developed by Suharti. Data were analyzed descriptively and statistically through normality test, Wilcoxon test with =0.05, and N-gain test. The results showed that the GITTW learning strategy had an effective effect, and can be applied by the teacher as an alternative learning strategy.

Self-Supervised Monocular Depth Estimation With Geometric Prior and Pixel-Level Sensitivity

Self-supervised monocular depth estimation has gained popularity due to its convenience of training network without dense ground truth depth annotation. Specifically, the multi-frame monocular depth estimation achieves promising results in virtue of temporal information. However, existing multi-frame solutions ignore the different impacts of pixels of input frame on depth estimation and the geometric information is still insufficiently explored. In this paper, a self-supervised monocular depth estimation framework with geometric prior and pixel-level sensitivity is proposed. Geometric constraint is involved through a geometric pose estimator with prior depth predictor and optical flow predictor. Further, an alternative learning strategy is designed to improve the learning of prior depth predictor by decoupling it with the ego-motion from the geometric pose estimator. On this basis, prior feature consistency regularization is introduced into the depth encoder. By taking the dense prior cost volume based on optical flow map and ego-motion as the supervising signal for feature consistency learning, the cost volume is obtained with more reasonable feature matching. To deal with the pixel-level difference of sensitivity in input frame, a sensitivity-adaptive depth decoder is built by flexibly adding a shorter path from cost volume to the final depth prediction. In this way, the back propagation of gradient to cost volume is adaptively adjusted, and an accurate depth map is decoded. The effectiveness of the proposed method is verified on public datasets.

Resonant learning in scale-free networks.

Large networks of interconnected components, such as genes or machines, can coordinate complex behavioral dynamics. One outstanding question has been to identify the design principles that allow such networks to learn new behaviors. Here, we use Boolean networks as prototypes to demonstrate how periodic activation of network hubs provides a network-level advantage in evolutionary learning. Surprisingly, we find that a network can simultaneously learn distinct target functions upon distinct hub oscillations. We term this emergent property resonant learning, as the new selected dynamical behaviors depend on the choice of the period of the hub oscillations. Furthermore, this procedure accelerates the learning of new behaviors by an order of magnitude faster than without oscillations. While it is well-established that modular network architecture can be selected through evolutionary learning to produce different network behaviors, forced hub oscillations emerge as an alternative evolutionary learning strategy for which network modularity is not necessarily required.

Constrained Center Loss for Convolutional Neural Networks.

From the feature representation's point of view, the feature learning module of a convolutional neural network (CNN) is to transform an input pattern into a feature vector. This feature vector is then multiplied with a number of output weight vectors to produce softmax scores. The common training objective in CNNs is based on the softmax loss, which ignores the intra-class compactness. This brief proposes a constrained center loss (CCL)-based algorithm to extract robust features. The training objective of a CNN consists of two terms, softmax loss and CCL. The aim of the softmax loss is to push the feature vectors from different classes apart. Meanwhile, the CCL aims at clustering the feature vectors such that the feature vectors from the same classes are close together. Instead of using stochastic gradient descent (SGD) algorithms to learn all the connection weights and the cluster centers at the same time. Our CCL-based algorithm is based on the alternative learning strategy. We first fix the connection weights of the CNN and update the cluster centers based on an analytical formula, which can be implemented based on the minibatch concept. We then fix the cluster centers and update the connection weights for a number of SGD minibatch iterations. We also propose a simplified CCL (SCCL) algorithm. Experiments are performed on six commonly used benchmark datasets. The results demonstrate that the two proposed algorithms outperform several state-of-the-art approaches.

Efforts to Improve the Development of Early Childhood Cognitive Ability in Kindergarten Ade Irma Mataloko

The practice activity of the teaching experience is a practice activity wherestudents train to become actual teachers. This is one of the most exciting activities because whenwe apply for the practice of teaching at the school the teacher will surely give us a full opportunity which means they give us the opportunity to teach the children. This teaching activity aims: (1) knowing the learning media design to increase children's cognitive cognitive at TKK ade Irma mataloko, (2) produces media that is practical to enhance children's cognitive abilities in TKK ade Irma mataloko. The recommendation of this research is that teachers are expected to consider implementing the methods of projects using the surroundings as alternative learning strategies especially in improving the children's cognitive in TK ADE MATALOKO.

A multi-criteria decision-making (MCDM) approach for data-driven distance learning recommendations.

Distance learning has been adopted as an alternative learning strategy to the face-to-face teaching methodology. It has been largely implemented by many governments worldwide due to the spread of the COVID-19 pandemic and the implication in enforcing lockdown and social distancing. In emergency situations distance learning is referred to as Emergency Remote Teaching (ERT). Due to this dynamic, sudden shift, and scaling demand in distance learning, many challenges have been accentuated. These include technological adoption, student commitments, parent involvement, and teacher extra burden management, changes in the organization methodology, in addition to government development of new guidelines and regulations to assess, manage, and control the outcomes of distance learning. The objective of this paper is to analyze the alternatives of distance learning and discuss how these alternatives reflect on student academic performance and retention in distance learning education. We first, examine how different stakeholders make use of distance learning to achieve the learning objectives. Then, we evaluate various alternatives and criteria that influence distance learning, we study the correlation between them and extract the best alternatives. The model we propose is a multi-criteria decision-making model that assigns various scores of weights to alternatives, then the best-scored alternative is passed through a recommendation model. Finally, our system proposes customized recommendations to students, and teachers which will lead to enhancing student academic performance. We believe that this study will serve the education system and provides valuable insights and understanding of the use of distance learning and its effectiveness.

Design of Science Process Skill-Based Intertextual Learning on Reaction Kinetics Concept

The study aims to design an intertextual learning strategy with Predict-observe-explain (POE) to develop students' science process skills. The research method is Research and Development (R&D) consist of material analysis, developing indicators of science process skills, and developing learning designs. The learning design was validated by five experts. Based on experts’ suggestion, intertextual-based learning activities involving three levels of chemical representation with POE learning steps to build the concept of the effect of the nature of the reactant and catalyst on reaction rates and develop students' science process skills. The strategy consists of five phenomena which are followed by three experiments and two videos as observation tools for the student. The explanation stages are guided by sets of guiding questions that involve multi-representation levels in that explanation. The product of this research is expected to be used as an alternative learning strategy that can be used by teachers to minimize the possibility of misconceptions that occur, increase mastery of concepts, and students' science process skills.

Assessing Learning Management System (LMS) for The Dairy Farmer: Obstacles to Delivering Online Learning Content

Online learning is currently an alternative learning strategy for continuous learning amidst the limitations of face-to-face learning due to the spread of the Covid-19 outbreak. However, the implementation of online learning certainly does not only provide solutions but also provides obstacles in its implementation which results in the non-delivery of learning content in online learning. Of course this can have an impact on dairy farmers as new users of the Learning Management System. This study aims to analyze the constraints of online learning based on the responses that have been shared by Twitter social media users towards the implementation of online learning and to assess the use of LMS for dairy farmers. This study uses the Twitter data crawling method on Twitter social media user responses to the topic of online learning constraints and data visualization to analyze LMS usage by . The research findings state that most users of online learning complain about internet quota constraints and the technical constraints experienced by them resulting in learning content not being absorbed optimally. This research can enrich research related to the use of social media data as data that can be analyzed and documented for learning development.

Model Pembelajaran Kooperatif Team Games Tournament dalam Pembelajaran Mahārah Kitābah di Perguruan Tinggi

The study aims to describe TGT (Team Games Tournament) cooperative learning model as an alternative learning strategy to increase student motivation and creativity in various aspects of language skills, including Arabic. This research method uses qualitative and quantitative research. The subjects in this study were students majoring in Madrasah Ibtidaiyah Teacher Education at STAI Al-HIKAM Malang. Data collection techniques in this study were obtained through observation, interviews, and documentation. The research instrument used the implementation observation sheet. The results of this study are: a) Based on the presence and recap of the student learning outcomes score sheet. b) Based on the structured interview sheet the implementation of the students after using the TGT (Team Games Tournament) cooperative learning model for Arabic language learning. The study results indicate that learning using the TGT (Team Games Tournament) learning model can improve Arabic learning abilities by making students more active and enthusiastic in the learning process.

Implementation of blended learning model in the ISMUBA curriculum during Covid-19 Pandemic

The learning model during the pandemic has changed along with the prohibition of face-to-face to avoid transmission of the Corona virus. This has led to various adjustments by teachers and students to keep the curriculum running, including the ISMUBA curriculum. This study aims to describe the implementation of blended learning in the ISMUBA curriculum as a form of adjustment during a pandemic. Since the implementation of learning from home, the blended learning method is the right method to be used in this day. Blended learning is a combination of face-to-face learning and learning that utilizes affirmation technology in its implementation. This study used a qualitative descriptive method, all data in this study were obtained through a series of interviews with informant. The informant is ISMUBA teacher. The results showed that blended learning can be used as an alternative learning strategy in the ISMUBA curriculum.

Supporting Future Teachers to Promote Computational Thinking Skills in Teaching STEM—A Case Study

In recent years, teachers in various fields, such as science, mathematics, linguistics and others, have been interested in alternative learning strategies as opposed to traditional activities, in order to help students to examine their learning progress. The integration of computational thinking in teaching activities, after returning to face-to-face activities, can meet the needs of students during the COVID-19 pandemic. In this research, two samples of students in their first year of study were recruited for the teacher training program validation for computational skills in STEM education. The training model offers an explanation for the differences between the following two sets of data: the CT modules used in a substantial number of teacher workshops, and the results obtained, which are closely related to the argument that teachers can support students’ lifelong learning by developing computational thinking activities. The results related to the students’ scores may have contributed to their improvement in computational thinking skills and it could be one of the best examples of how to change the ways of learning about 21st century skills and sustainable education.

Anatomy education beyond the Covid-19 pandemic: A changing pedagogy.

The coronavirus disease 2019 (Covid‐19) pandemic has induced multifaceted changes in anatomical education. There has been a significant increase in the employment of digital technologies coupled with the upskilling of educators' capacity and altered attitudes toward the digitalization process. While challenges remain, learners have demonstrated capabilities to adapt to digital delivery, engagement and assessment. With alternative and innovative teaching and learning strategies having been trialed and implemented for almost two years, the key question now is what the pedagogy will be for anatomy education beyond the pandemic. Here we discuss some of the changes in anatomy education that have taken place as a result of the Covid‐19 pandemic and importantly present some outlooks for evidence‐based anatomy pedagogy as the world enters the post‐pandemic phase and beyond. The authors conclude that the anatomy discipline is ready to further modernize and has the opportunity to use digital technologies to evolve and enhance anatomy education to ensure students are provided with the learning experience which will prepare them best for the future.

Project-based learning model to promote students critical and creative thinking skills

This study aimed to assess the worthiness of the project-based learning model in training critical and creative thinking skills on colloidal material. This research is a pre-experimental design with a one group pretest-posttest design. 31 students of XI MIPA 4 at MAN 1 Mojokerto were the targets studied in this study. The results of this study are: 1) The average percentage of the project-based learning treatment obtained is 78% in the good category (1st meeting) and 88% in the very good category (2nd meeting). 2) The activity of students is declared good with a percentage of 88%. 3) Critical and creative thinking skills have high criteria, as shown in the results of N-Gain 0.70, 0.73, and 0.73. 4) Student learning outcomes increase, which indicated from one complete student to 28 complete students. 5) A total of 95% positive responses were obtained from 31 students on the Project-Based Learning model. So the conclusion that can be drawn is that the project based learning model can train students' critical and creative thinking skills on colloidal material. project based learning model can be used as an alternative learning strategy to practice critical and creative thinking skills as the demands of 21st-century skills. It is more maximal and meaningful so that the desired learning activities and better results study can be achieved.

If online learning works for you, what about deaf students? Emerging challenges of online learning for deaf and hearing-impaired students during COVID-19: a literature review.

With the coronavirus (COVID-19) outbreak, educational systems worldwide were abruptly affected and hampered, causing nearly total suspension of all in-person activities in schools, colleges, and universities. Government officials prohibited the physical gatherings in educational institutions to reduce the spread of the virus. Therefore, educational institutions have aggressively shifted to alternative learning methods and strategies such as online-based platforms—to seemingly avoid the disruption of education. However, the switch from the face-to-face setting to an entirely online setting introduced a series of challenges, especially for the deaf or hard-of-hearing students. Various recent studies have revealed the underlying infrastructure used by academic institutions may not be suitable for students with hearing impairments. The goal of this study is to perform a literature review of these studies and extract the pressing challenges that deaf and hard-of-hearing students have been facing since their transition to the online setting. We conducted a systematic literature review of 34 articles that were carefully collected, retrieved, and rigorously categorized from various scholarly databases. The articles, included in this study, focused primarily on highlighting high-demanding issues that deaf students experienced in higher education during the pandemic. This study contributes to the research literature by providing a detailed analysis of technological challenges hindering the learning experience of deaf students. Furthermore, the study extracts takeaways and proposed solutions, from the literature, for researchers, education specialists, and higher education authorities to adopt. This work calls for investigating broader and yet more effective teaching and learning strategies for deaf and hard-of-hearing students so that they can benefit from a better online learning experience.

Improved Understanding of Science Concepts in Terms of the Pattern of Concept Maps Based on Scientific Literacy in Prospective Elementary School Teacher Students

Concept maps are a technique that can represent the knowledge possessed by students. Depiction through concept maps can form a structured and systematic understanding of concepts based on the relationships between the written concepts. In a period of online learning like this, an exciting learning strategy is needed. Therefore, using concept maps can be an alternative learning strategy that lecturers can apply in online learning. This study aims to identify various concept map patterns that students often use to improve conceptual understanding of the topic of global warming as well as increase students' conceptual understanding of the draft concept map patterns. This research is a mixed-method type with concurrent embedded with 83 students of Primary Teacher Education semester 2 of the 2019/2020 academic year. The instrument used was the measurement instrument for the concept map pattern and the measurement of the conceptual understanding test based on scientific literacy for students. The results were then analyzed by normalized N-Gain test and qualitative data analysis. The results showed that students' concept map patterns to improve conceptual understanding using the hub/spokes concept map pattern were 87.9%. Meanwhile, the results of the N-Gain analysis showed several 0.53 (in the medium category), which means that understanding of the concept increases with the application of concept map learning. The concept map pattern that appears depicts the results of the visualization of students' conceptual understanding