Relevant bibliographies by topics / Brain-based learning strategies

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Brain-based learning strategies'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Brain-based learning strategies"

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Doolen, Jessica. "Embracing Brain-Based Teaching and Learning Strategies." Clinical Simulation in Nursing 10, no. 10 (October 2014): 491–93. http://dx.doi.org/10.1016/j.ecns.2014.08.002.

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Coffman, Teresa L., and Mary Beth Klinger. "Collaboration and Communication in the Online Classroom through a Brain-Based Approach." International Journal of Information Communication Technologies and Human Development 6, no. 3 (July 2014): 42–52. http://dx.doi.org/10.4018/ijicthd.2014070104.

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Utilizing brain-based learning strategies in the classroom encourages the creation of learning environments that are inviting, engaging, and meaningful. Information and communication technologies used in online classes can be enhanced and made more meaningful for students by applying a brain-based approach. This paper examines the use of brain-based learning in an online environment to build an inviting and collaborative cultural experience for learners. A brain-based model is explored to illustrate effective teaching strategies that can be implemented in an online learning environment. Empirical research and analysis are presented in a research study along with a theoretical evaluation of how incorporating brain-based strategies in online learning can positively affect overall student development and online culture.
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Brédart, Serge. "Strategies to Improve Name Learning." European Psychologist 24, no. 4 (October 2019): 349–58. http://dx.doi.org/10.1027/1016-9040/a000363.

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Abstract. The following points emerge from the present review of strategies to improve the learning of proper names: (a) Face-name mnemonic techniques based on mental imagery have been shown to be efficient in laboratory settings in both young and older adults. Unfortunately, they are particularly effortful and require capacity for imagination, making them difficult to apply in a real conversational context. (b) Strategies based on spaced retrieval practice have been found to be efficient both in laboratory and more ecological settings, and both in young and older adults. (c) Techniques based on spaced retrieval practice appear to be more efficient than those based on mental imagery. (d) More recent research has proposed new perspectives, such as basing learning strategies on implicit, rather than explicit, memory processes such as hyper-binding. Finally, neuroscience research has started to investigate the possibility of using non-invasive electrical brain stimulation to improve name learning.
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Restaino, Rusti. "Gain Attention, Enhance Memory, and Improve Learning with Brain-Based Strategies." Journal of Continuing Education in Nursing 42, no. 5 (May 1, 2011): 199–200. http://dx.doi.org/10.3928/00220124-20110421-04.

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Fatima, Hafiza Gulnaz, Uzma Quraishi, and Afifa Khanam. "Applying Brain Based Learning Modules for Learning Acceleration of 6th Grade Science Students." sjesr 3, no. 1 (April 19, 2020): 27–34. http://dx.doi.org/10.36902/sjesr-vol3-iss1-2020(27-34).

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This pre-test post-test control group experimental study was conducted to identify difference in the performance of three BBL (Brain Based Learning) types of strategies; practical simulation, problem solving and cooperative learning on early elementary graders. The modules were developed by the researchers to find the effectiveness of BBL strategies over traditional chalk and talk method. The study involved three pairs of control and experimental groups randomly of sixth graders having N=30 each and total 180 students from district Lahore public schools. The students received intervention for four months for 4 chapters of 6th grade General Science subject. All students were pre and post tested by a 40 item multiple choice concept based achievement test. The pre and post test scores of all control and experimental groups were compared to find out the achievement difference of students through comparing their gain score (post-test – pre-test) after intervention. The study revealed that all the three BBL modules were effective because the intervention groups showed greater gain score parallel to their control groups.
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Sari, Suci Lupita, Destia Wahyu Hidayati, and Arie Wahyuni. "Penerapan Strategi Brain-Based Learning Berbantuan Geogebra Terhadap Kemampuan Berfikir Kreatif Siswa." Square : Journal of Mathematics and Mathematics Education 1, no. 1 (September 16, 2019): 13. http://dx.doi.org/10.21580/square.2019.1.1.4038.

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<p>The purpose of this study is to determine the average mathematical creative thinking ability of students by using Geogebra-assisted Brain-Based Learning strategies more than KKM (70) and to find out the average mathematical creative thinking ability of students using more Brain-Based Learning strategies assisted by Geogebra higher than students' creative mathematical thinking abilities using conventional methods. This research uses quantitative methods. The sample of this study was students of class VIII-A as many as 16 students as the experimental class and class VIII-B as many as 18 students as the control class. The results of this study indicate that students' creative thinking abilities using Geogebra-assisted Brain-Based Learning strategies are more than 70 and there are significant differences between the abilities of students who obtain conventional learning with students who learn with the Geogebra-Aided Brain-Based Learning model.</p><p class="JRPMAbstractBody" align="center"><strong><em> </em></strong></p>
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Sari, Suci Lupita, Destia Wahyu Hidayati, and Arie Wahyuni. "Penerapan Strategi Brain-Based Learning Berbantuan Geogebra Terhadap Kemampuan Berfikir Kreatif Siswa." Square : Journal of Mathematics and Mathematics Education 1, no. 1 (September 16, 2019): 13. http://dx.doi.org/10.21580/square.v1i1.4038.

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<p>The purpose of this study is to determine the average mathematical creative thinking ability of students by using Geogebra-assisted Brain-Based Learning strategies more than KKM (70) and to find out the average mathematical creative thinking ability of students using more Brain-Based Learning strategies assisted by Geogebra higher than students' creative mathematical thinking abilities using conventional methods. This research uses quantitative methods. The sample of this study was students of class VIII-A as many as 16 students as the experimental class and class VIII-B as many as 18 students as the control class. The results of this study indicate that students' creative thinking abilities using Geogebra-assisted Brain-Based Learning strategies are more than 70 and there are significant differences between the abilities of students who obtain conventional learning with students who learn with the Geogebra-Aided Brain-Based Learning model.</p><p class="JRPMAbstractBody" align="center"><strong><em> </em></strong></p>
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Mastoni, Edy. "The Brain Based Learning (BBL) and Intrapersonal Intelligence for Mathematics Learning in Junior High School." Asia Proceedings of Social Sciences 4, no. 3 (April 26, 2019): 17–19. http://dx.doi.org/10.31580/apss.v4i3.815.

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Research Highlights The study proposed two focus studies and results indicated there is a conformity between Brain Based Learning (BBL) and students' intrapersonal intelligence toward characteristics of junior high school mathematics learning. Implementation of Brain Based Learning (BBL) and intrapersonal intelligence in junior high school mathematics learning can improve student’s learning outcomes. Research Objectives This research aims to knowing activities of junior high school mathematics learning and to knowing conformity of characteristics between Brain Based Learning (BBL) and intrapersonal intelligence with junior high school mathematics learning. BBL as a learning strategies and intrapersonal intelligence as an internal factors of students must be the main consideration in learning activities, including in this case mathematics learning. Learning is more directed at construction than instruction, which has implications for the role of teachers and students (Reigeluth and Carr-Chellman, 2009). Learning strategies concept is a various types of plans used by the teacher to achieve goals (Silver et al., 2012). In simple terms, this view states that learning strategies are ways to do something in achieving goals. Learning mathematics is learning about the concepts and structure of mathematics and looking for relationships between the two on the material being studied (Bruner, 2009). In the learning activities, learning materials must be adapted to the abilities and cognitive structures of students. Learning material must be related to the concepts that are already owned so that new ideas can be fully absorbed by students (Ausubel, 2012). Learning activities must be gradual, sequential and always based on past learning experiences. Methodology This type of research is qualitative descriptive. The approach used is qualitative with descriptive methods and literature studies. Data collection uses documentation studies, observations, and interviews with teachers and students. Data collection was conducted in junior high school of SMP Assahil Lampung Timur in the 2018/2019 academic year. The mathematics teachers and students were included in this study as a respondents. In this study the data analysis used was quantitative descriptive and qualitative descriptive analysis. Quantitative descriptive analysis is used to present and analyze data relating to mathematics learning outcomes over the past three years. Qualitative descriptive analysis is used to interpret and analyze data regarding the learning process of mathematics that has taken place. Results The study indicate that mathematics teachers have only used expository learning strategies in learning activities. The expository learning strategy is a form of teacher-centered learning approach. Mathematical learning outcomes are not satisfactory. The Mathematics learning is a learning process that involves active students building mathematical knowledge (Cobb, 2013). In mathematics learning there is a process of developing students' creativity to improve their abilities and beliefs in building knowledge and mastering good mathematics subject matter. The Characteristics of Brain Based Learning (BBL) emphasizes students to play an active role in building the concepts learned (Ulger, 2018). The steps in the BBL learning strategy include creating a learning environment that challenges students' thinking skills (regulated immersion), creates a relaxed learning environment, and creates actual and meaningful learning situations for students (active processing). Intrapersonal intelligence is self-knowledge as intelligence that involves self-awareness or self-sensitivity, thought processes, realizing changes that occur in oneself, involving skills of cooperation and communication both verbally and nonverbally (Alder, 2001). The characteristics of intrapersonal intelligence consist of three main aspects that can be used as benchmarks, namely recognizing oneself, knowing one's own desires, and knowing what is necessary for oneself. Findings The results of data analysis, it was found that the learning activities that had taken place so far only used expository learning strategies. The teacher does not apply learning strategies that are in accordance with the internal factors of students in learning mathematics. The literature review show that there is a match between the characteristics of junior high school mathematics material, the characteristics of BBL learning strategies and the characteristics of intrapersonal intelligence. Therefore, the implementation of BBL learning strategies and intrapersonal intelligence in junior high school mathematics learning is very well done to improve student learning outcomes. Acknowledgement This study was supported by Universitas Negeri Jakarta and SMP Assahil Lampung Timur, for which thanks to 1) Doctoral Program in Educational Technology, Postgraduate Program at Universitas Negeri Jakarta; 2) SMP Assahil Lampung Timur; 3) Prof. Dr. M. Syarif Sumantri, M.Pd. as the promoter and Prof. Dr. Nurdin Ibrahim, M.Pd. as the co. promoter who has provided guidance to the author.
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Hussain, Lal, Sharjil Saeed, Imtiaz Ahmed Awan, Adnan Idris, Malik Sajjad Ahmed Nadeem, and Qurat-ul-Ain Chaudhry. "Detecting Brain Tumor using Machines Learning Techniques Based on Different Features Extracting Strategies." Current Medical Imaging Formerly Current Medical Imaging Reviews 15, no. 6 (July 5, 2019): 595–606. http://dx.doi.org/10.2174/1573405614666180718123533.

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Background: Brain tumor is the leading cause of death worldwide. It is obvious that the chances of survival can be increased if the tumor is identified and properly classified at an initial stage. MRI (Magnetic Resonance Imaging) is one source of brain tumors detection tool and is extensively used in the diagnosis of brain to detect blood clots. In the past, many researchers developed Computer-Aided Diagnosis (CAD) systems that help the radiologist to detect the abnormalities in an efficient manner. Objective: The aim of this research is to improve the brain tumor detection performance by proposing a multimodal feature extracting strategy and employing machine learning techniques. Methods: In this study, we extracted multimodal features such as texture, morphological, entropybased, Scale Invariant Feature Transform (SIFT), and Elliptic Fourier Descriptors (EFDs) from brain tumor imaging database. The tumor was detected using robust machine learning techniques such as Support Vector Machine (SVM) with kernels: polynomial, Radial Base Function (RBF), Gaussian; Decision Tree (DT), and Naïve Bayes. Most commonly used Jack-knife 10-fold Cross- Validation (CV) was used for testing and validation of dataset. Results: The performance was evaluated in terms of specificity, sensitivity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), False Positive Rate (FPR), Total Accuracy (TA), Area under the receiver operating Curve (AUC), and P-value. The highest performance of 100% in terms of Specificity, Sensitivity, PPV, NPV, TA, AUC using Naïve Bayes classifiers based on entropy, morphological, SIFT and texture features followed by Decision Tree classifier with texture features (TA=97.81%, AUC=1.0) and SVM polynomial kernel with texture features (TA=94.63%). The highest significant p-value was obtained using SVM polynomial with texture features (P-value 2.65e-104) followed by SVM RB with texture features (P-value 1.96e-98). Conclusion: The results reveal that Naïve Bayes followed by Decision Tree gives highest detection accuracy based on entropy, morphological, SIFT and texture features.
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Pilcher, Jobeth. "Education and Learning: What’s on the Horizon?" Neonatal Network 33, no. 1 (2013): 24–28. http://dx.doi.org/10.1891/0730-0832.33.1.24.

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Numerous organizations have called for significant changes in education for health care professionals. The call has included the need to incorporate evidence-based as well as innovative strategies. Previous articles in this column have focused primarily on evidence-based teaching strategies, including concept mapping, brain-based learning strategies, methods of competency assessment, and so forth. This article shifts the focus to new ways of thinking about knowledge and education. The article will also introduce evolving, innovative, less commonly used learning strategies and provide a peek into the future of learning.
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Dissertations / Theses on the topic "Brain-based learning strategies"

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Sperlich, Juntana Ginda. "Designing a brain-based learning environment." CSUSB ScholarWorks, 2007. https://scholarworks.lib.csusb.edu/etd-project/3216.

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The purpose of this project was to develop a teacher friendly guide that would help teachers not only apply brain-based strategies in the classroom, but also to see results from transforming their classrooms into brain-based learning environments.
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Swedlund, Margo R. "Increasing elementary level academic performance through brain-based teaching strategies." Online version, 2003. http://www.uwstout.edu/lib/thesis/2003/2003swedlundm.pdf.

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Szabados, Cynthia Grassel. "Utilizing the principles and strategies of brain based learning in educating the deaf." CSUSB ScholarWorks, 2003. https://scholarworks.lib.csusb.edu/etd-project/2405.

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Klinek, Shelly R. "Brain-based learning knowledge, beliefs, and practices of college of education faculty in the Pennsylvania State System of Higher Education /." Open access to IUP's electronic theses and dissertations, 2009. http://hdl.handle.net/2069/150.

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Uster, Sema. "The Role Of Gender-based Brain Differences On The Vocabulary Learning And Consolidation Skills And Strategies." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12610252/index.pdf.

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ABSTRACT This study aims to investigate the possible relationship between the differences of the male and female brain and vocabulary learning strategies of male and female students. For this purpose, a study has been carried out with a group of 200 students attending the Preparatory Program at TOBB University of Economics and Technology. This study initially aims to identify the differences between the biology of the male and female brain as well as the hormones influencing the memory and vocabulary retention. This information will then be applied to the vocabulary learning strategies of males and females. In order to identify the strategies used by males and females, a questionnaire was administered to a group of students attending the Preparatory Program at TOBB Economy and Technology University. Before the main study, the questionnaire was administered as a pilot study with 50 students from the same achievement group. After the pilot study of the questionnaire
validity, reliability and factor analysis studies were carried out. All of these subjects were at the same level of proficiency. The relationship between the genders and their vocabulary learning strategies was studied according to the results of the study through statistical evaluation through t-test analysis on SPSS. The data collected through the questionnaire were analyzed by comparing them to the literature suggesting the differences between the male and female brain characteristics. As the result of this study, it has been found out that females use more variety of strategies than males. Females have been found to employ determination, social, and cognitive strategies more frequently than males while males employ memory strategies more than females. In addition, there was not a statistically significant difference between the use of metacognitive strategies of male and female participants.
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Williams, Marian H. (Marian Haile). "The Effects of a Brain-based Learning Strategy, Mind Mapping, on Achievement of Adults in a Training Environment with Considerations to Learning Styles and Brain Hemisphericity." Thesis, University of North Texas, 1999. https://digital.library.unt.edu/ark:/67531/metadc278776/.

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This study examined the effectiveness of Mind Mapping (a diagram of the structure of ideas in an associative manner, using graphics, color and key words) as a note-taking device in a training course in a large, high-tech corporation, as compared to traditional note-taking. The population for this study consisted of personnel employed by a major high-tech firm, that had voluntarily registered for a Mind Mapping training class. The effect of Mind Mapping was measured by the pre-test and post-test of the control and experimental groups.
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White, Dan, and res cand@acu edu au. "Pedagogy – The Missing Link in Religious Education: Implications of brain-based learning theory for the development of a pedagogical framework for religious education." Australian Catholic University. School of Religious Education, 2004. http://dlibrary.acu.edu.au/digitaltheses/public/adt-acuvp60.29082005.

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Over the past three decades, the development of religious education in Australia has been largely shaped by catechetical and curriculum approaches to teaching and learning. To date, little emphasis has been placed on the pedagogical dimension of religious education. The purpose of this research project is to explore the manner in which ‘brain-based’ learning theory contributes to pedagogical development in primary religious education. The project utilises an action research methodology combining concept mapping, the application of ‘brain-based’ teaching strategies and focus group dialogue with diocesan Religious Education Coordinators (RECs). The insights derived contribute to the formulation and validation of an appropriate pedagogical model for primary religious education, entitled the ‘DEEP Framework’. The model reflects an integration of insights from brain-based theory with nuances from the contemporary Australian religious education literature. The project identifies four key, interactive principles that are crucial to pedagogical development in religious education, namely: Discernment, Enrichment, Engagement and Participation. It also recognises a fifth principle, ‘an orientation towards wholeness’, as significant in combining the various pedagogical principles into a coherent whole. The DEEP framework enables teachers to more successfully select and evaluate appropriate, interconnecting teaching strategies within the religious education classroom. The framework underpins the pedagogical rationale of the recently developed Archdiocese of Hobart religious education program and forms the basis for the implementation of a coherent professional development program across the Archdiocese.
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Scott, Margaret M. "The efficacy of holistic learning strategies in the development of church leaders in Mozambique : an action research approach." Thesis, 2006. http://hdl.handle.net/2263/29452.

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This Participatory Action Research (PAR) project focused on “holistic learning” which includes “social” and “spiritual” learning and “whole-brained” learning. Broadly interpreting and applying the four-quadrant brain model of Herrmann (1994), and other models of the brain, my study seeks to understand whether, to what extent and how learning can be advanced by deliberately employing holistic learning strategies to narrow the gap between theory and practice, between left-brain and right-brain learning, and between cognition and emotion. I introduced tri-dimensional (3-D) practice as the combination of using holistic learning strategies in cooperative learning groups within spiritual learning environments. The site of this PAR study was the network of cooperative learning groups in Mozambique within the educational system of the Church of the Nazarene. Facilitators were trained to use six specific “holistic learning strategies”: group discussions of various types, praxis (as reflection-dialogue-action), teamwork, rehearsing integrity, singing-for-learning and classical spiritual disciplines within cooperative learning groups, also a holistic learning strategy. These aspects are typical of the widely used model of Theological Education by Extension (TEE), refined in this study. According to data gathered in a large hybrid survey, 97% of the 595 respondents to this question responded favourably in terms of the skills of these facilitators even though the average number of years of their formal schooling, 7.7, would normally be considered “minimal”. The study generates findings to support the position that holistic learning strategies enhance the quality of adult learning, at least in settings like those in Mozambique in which the facilitation of learning was 1) bilingual (Portuguese and maternal language), 2) focused on learners who are leaders-in-training, 3) deliberate in spiritual content and ambient, and 4) conducted by minimally-schooled facilitators in cooperative learning groups. The findings, from the responses recorded in qualitative phases of the research, corroborated by descriptive statistics, indicate that the efficacy of holistic learning strategies is related to certain modes of mental activity like whole-making, categorising, and others. This PAR project was conducted within an original research framework, Arboric Research, which takes into account the dynamic, fluid and organic nature of human systems, recognising that infrastructures in which the research takes place are different at the end of the study than at the beginning, like observing the “sap” within a growing grapevine or a tree.
Thesis (PhD (Curriculum Studies))--University of Pretoria, 2006.
Curriculum Studies
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WU, CHIA-CHEN, and 武佳箴. "The Correlation between Language Learning Strategies and Second Language Collocation Learning – Based on the study of Event-Related Brain Potentials." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/pn46p5.

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Machobane, Amohelang Masibongile. "Strategies for facilitating learning in Adult Basic Education and Training." Diss., 2010. http://hdl.handle.net/2263/27925.

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This study examines the strategies used by facilitators at Adult Basic Education and Training Centre in order to determine whether the facilitators are responsive to adult learning principle and practices. If inappropriate strategies for the facilitation of learning are used, adult learners are likely to become bored, frustrated, overwhelmed or unable to cope with the challenges of learning. This may contribute to the high drop-out rate that many adult education programmes face. The failure to retain adult learners in ABET programmes may result in adult learners relapsing into illiteracy, which then poses a problem as the overarching goal of the South African government is to eradicate illiteracy. This study aims at answering the following research questions:
  • What are the perceptions of adult learners of the facilitation of learning in the programmes they are enrolled for?
  • What are the strategies used by ABET facilitators to promote cooperative learning?
  • How do ABET facilitators promote self-directed learning among adult learners?
The theoretical framework on which this study is based is constructivism. Constructivist theory advocates a paradigm shift from traditional methods of teaching to a more learner-centred approach of instruction and learning. Thus, constructivist theory embraces Outcomes-based Education that emphasises that active participation by learners should be the backbone of all learning activities. Both facilitators and learners are required to focus on the outcomes that should be achieved during each learning activity. This study employs a mixed-methods approach that includes quantitative and qualitative research methods. The research design for this study is the case study method. The population of this study comprises adult learners and facilitators at Gaegolelwe Adult Centre. A simple random sampling was used to select forty-seven adult learners to participate in this study. Convenience sampling was used to select 4 facilitators. The methods of data collection used were questionnaires, semi-structured interviews and observations. The findings of this study are the following:
  • Facilitators at Gaegolelwe Adult Centre cater moderately for learners with different learning styles.
  • Learners are engaged in different learning activities, such as completing tasks individually, in pairs or in groups and are involved in research orientated activities in order to discover things for themselves.
  • Facilitators promote active participation during learning opportunities.
  • Most adult learners demonstrate responsibility towards their own work. However, some do not, and this may be attributed to many competing social roles that must be balanced against the demands of learning.
  • Learners are challenged to develop critical thinking, problem-solving and higher order reasoning skills.
  • Cooperative learning as one strategy of facilitating learning is not utilised to the maximum.
  • It has been observed that the lecture method is predominantly used by facilitators; this is not in line with constructivist learning theory as the latter emphasises the use of different methods of facilitation in order to accommodate learners with diverse learning styles.
The following recommendations have been made:
  • Facilitators with extensive teaching experience should be engaged to facilitate adult learning. However, they should be educated and trained in methods of facilitating adult learners.
  • Male adults need to be mobilised through mass literacy campaigns to join ABET programmes.
  • Learners should be given the opportunity to make an input in the development of strategies for facilitating learning.
Copyright
Dissertation (MEd)--University of Pretoria, 2010.
Early Childhood Education
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Books on the topic "Brain-based learning strategies"

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Harrison, Connie. Brain-based study strategies: A guide for adult learners. Port Huron, Mich: Baker College, 2009.

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Sanchez, Horacio. A Brain-based approach to closing the achievement gap. [S.l.]: Xlibris Corp, 2008.

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40 engaging brain-based tools for the classroom. Thousand Oaks, CA: Corwin Press, 2009.

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Willis, Judith A. Inspiring middle school minds: Gifted, creative, & challenging brain research-based strategies to enhance learning for gifted students. Scottsdale, AZ: Great Potential Press, 2009.

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Inspiring middle school brains: Gifted, creative, challenging brain research-based strategies to enhance learning for gifted students. Scottsdale, AZ: Great Potential Press, 2009.

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Secrets of the teenage brain: Research-based strategies for reaching and teaching today's adolescents. 2nd ed. Thousand Oaks, Calif: Corwin Press, 2009.

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Willis, Judy. Research-Based Strategies to Ignite Student Learning. Alexandria: ASCD, 2009.

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Ronis, Diane L. Brain-compatible mathematics. Arlington Heights, IL: SkyLight Training and Pub., 1999.

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Brain-compatible mathematics. 2nd ed. Thousand Oaks, Calif: Corwin Press, 2007.

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Learning to Write for Readers: Using brain-based strategies. NCTE (National Council of Teachers of English), 2011.

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Book chapters on the topic "Brain-based learning strategies"

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Chai, Meei Tyng, Aamir Saeed Malik, Mohamad Naufal Mohamad Saad, and Mohammad Abdul Rahman. "Application of Digital Technologies, Multimedia, and Brain-Based Strategies." In Research Anthology on Adult Education and the Development of Lifelong Learners, 837–60. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8598-6.ch042.

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Teaching adult learners is challenging because the characteristics of adult learners and their expectations are different from children/early adolescence. Recent advances in digital technology offer various opportunities that are particularly useful in fostering adult learning by transforming traditional “live” classroom-based into “virtual.” This chapter aims to explore how the digital technologies affect the way the brain learns and memorizes, including cognitive, emotional, and behavioral dimensions to promote personal and professional development. First, this chapter presents the application of digital technologies that support and engage adult learners in enhancing knowledge acquisition and retention, discusses the specific engagement techniques for adult, along with the research on multimedia learning. This chapter also covered neuroscience studies related to brain-based learning and strategies. The opportunities and challenges of the use of digital technology and multimedia platform to be effective learning tools for academic context and lifelong learning are also presented.
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El-Henawy, Walaa M. "The Effect of Brain-Based Professional Development on Shifting English Language Teachers' Pedagogical Perceptions." In Paradigm Shifts in 21st Century Teaching and Learning, 118–30. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-3146-4.ch008.

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Brain-based learning (BBL) represents a new paradigm for teaching 21st Century learners. This chapter introduces brain-based professional development (BBPD) that utilizes theories and key findings from the field of cognitive neuroscience. This chapter reviews brain-based approach to learning and brain-compatible strategies for teaching as well as how to design a BBL lesson plan. Additionally, the chapter highlights the significance of incorporating BBL in professional development especially for novice English language teachers on shifting English language teachers' pedagogical perceptions. It stresses the importance of educating teachers about the brain and introducing brain-based instructional strategies. Besides, future research directions and educational implications of brain-based instruction are provided particularly for English language teaching and classroom environment.
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"Space Representation and Gender Differences." In A Simplex Approach to Learning, Cognition, and Spatial Navigation, 23–28. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2455-7.ch003.

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Scientific literature highlighted gender differences in spatial orientation. In particular, men and women differ in terms of the navigational processes they use in daily life. Scientific literature highlighted that women use analytical strategies while men tend to use holistic strategies. According to classical studies, males show a net advantage at least in the two categories of mental rotation and spatial perception. Subsequently, brain-imaging studies have shown a difference between males and females in the activity of brain regions involved in spatial cognition tasks. What we can say with certainty is that, given the complex nature of the subprocesses involved in what we call spatial cognition, the gender differences recorded by numerous scientific studies conducted in this field are closely related to specific measured abilities. The evidence that emerges with certainty from diverse studies is, however, that of a huge variety of strategies that differ according to sex, context, purpose to reach, education, age, and profession. In the study presented here, the gender and age-related tests show a significant sex-based difference perspective-taking tasks, but there is no gender-based difference in the mental rotation task.
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Lim, Doo Hun, Sunyoung Park, Cho Hyun Park, and Chang Sung Jang. "Neuroscientific Approaches for Maintaining, Balancing, and Developing Mature Workers." In Strategies for Attracting, Maintaining, and Balancing a Mature Workforce, 85–111. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2277-6.ch004.

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As the aging population is rapidly increasing worldwide, keeping older workers to address the skilled labor shortage has been an important economic issue. This study pursues the current status of the older workforce in the U.S., identifies organizational support systems for mature workers, and proposes neuroscientific approaches and methods to maintain and develop effective mature workers through an integrative review of recent research findings in neuroscience and brain-based learning and development.
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Trinchero, Roberto. "Designing Intelligent Tutoring Systems With AI." In Handbook of Research on Teaching With Virtual Environments and AI, 540–57. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7638-0.ch023.

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This chapter describes the research problems inherent the design of effective intelligent tutoring systems (ITS) based on cognitive neuroscience research (brain-based approach) and evidence-based education. Effective student-ITS interaction requires a thorough understanding of the brain processes that underpin learning. The knowledge of these principles allows you to select optimal pedagogical strategies to monitor and guide the process. AI-based tutors have great potential in constantly adapting teaching content and tactics to the changing cognitive needs of the individual student in order to foster deep understanding, increase motivation, and develop a sense of self-efficacy in the learner. The brain-based approach can give ITSs a significant increase in effectiveness in promoting learning.
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Hertel, Ron, and Mona M. Johnson. "How the Traumatic Experiences of Students Manifest in School Settings." In Supporting and Educating Traumatized Students, edited by Eric Rossen, 27–44. Oxford University Press, 2020. http://dx.doi.org/10.1093/med-psych/9780190052737.003.0002.

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Throughout their lifetimes, people can face challenges from toxic stress and trauma that influence their lives at any place, at any time. To be most effective, educators must understand the impact of trauma on neurobiology and brain development, academic and cognitive skills, behavior, and social-emotional functioning. They must learn to adapt the learning environment and strategies for instruction accordingly with these elements in mind. This chapter presents evidence-based and researched strategies that educators can employ to address the impact of trauma. From an educator’s point of view, the most helpful approach is twofold: firstly, an educator must be self-aware of his or her ability to manage his or her own challenges before, secondly, beginning to address challenges in the lives of students and their families.
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Curry, Marjorie. "Culturally Responsive Math." In Theory and Practice: An Interface or A Great Divide?, 115–17. WTM-Verlag Münster, 2019. http://dx.doi.org/10.37626/ga9783959871129.0.23.

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Using the Ready for Rigor framework, Zaretta Hammond’s book Culturally Responsive Teaching and the Brain: Promoting Authentic Engagement and Rigor Among Culturally and Linguistically Diverse Students gives educators a neuroscience-based approach to closing the achievement gap. The Ready for Rigor framework consists of four strands: awareness, learning partnerships, information processing, and community building. Acknowledging that all four strands are paramount to culturally responsive teaching but restricting focus to information processing, this session will give participants examples of and strategies for making their mathematics lessons more culturally responsive. More specifically, participants will learn to game-ify it, story-ify it, and make it social.
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Hertel, Ron, and Mona M. Johnson. "How the Traumatic Experiences of Students Manifest in School Settings." In Supporting and Educating Traumatized Students, 23–36. Oxford University Press, 2012. http://dx.doi.org/10.1093/med:psych/9780199766529.003.0002.

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The impact of trauma resonates in schools and can impair learning as well as cause challenging classroom behaviors. This chapter defines trauma as a response to adverse life experiences that can negatively affect physical, emotional, academic, and intellectual functioning. Specifically, it describes the impact of trauma on neurobiology and brain development, as well as academic, cognitive, behavioral, and social/emotional functioning. It also outlines practical, applicable strategies for addressing classroom management as well as six specific principles for educators who seek to support the social/emotional and academic development of students impacted by trauma. Professional self-care is also outlined as a vital core practice necessary to assist teachers in consistently approaching students from a strength-based perspective.
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Dempsey, Jack, Amy K. Barton, Allison G. Dempsey, and Stephanie Chapman. "Neurodevelopmental Disorders Presenting in Early Childhood." In Pediatric Health Conditions in Schools, edited by Jack Dempsey, Amy K. Barton, Allison G. Dempsey, and Stephanie Chapman, 245–60. Oxford University Press, 2019. http://dx.doi.org/10.1093/med-psych/9780190687281.003.0014.

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Neurodevelopmental disorders are a group of conditions that manifest in early childhood and are associated with differences in brain development. They are associated with difficulties with learning, movement, language, or social behaviors. This chapter provides school-based clinicians with a broad overview of neurodevelopmental disorders that present in early childhood, with a particular focus on those associated with specific underlying medical conditions. The reviewed medical conditions and complications include genetic and congenital anomalies, cerebral palsy, and preterm birth. For each of the varying medical complications and conditions, the chapter discusses the assessment and management of the associated neurodevelopmental difficulties, with a focus on applications for the school setting. The chapter ends with a broad overview of school-based intervention strategies and approaches that are commonly implemented when working with children with neurodevelopmental disorders.
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McKeen, Heather. "Culturally Relevant Preparedness Using STEAM Integrative Teaching in the Classroom." In Handbook of Research on Assessment Practices and Pedagogical Models for Immigrant Students, 127–38. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-9348-5.ch008.

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Although there exist some studies that examine culturally relevant teaching and its positive impact on learning outcomes; overall, these studies are not abundant, and teachers are generally unaware of the educational frameworks that would allow them to apply their theoretical knowledge of culturally relevant preparedness in practice. In this respect, STEAM can be a perfect solution for reinforcing culturally relevant teaching at schools. First, culturally relevant teaching requires certain conditions (e.g., diversity, inclusion, a teacher's willingness to learn, etc.) that are inherent in the STEAM educational framework. Second, the STEAM educational framework shares similar values with culturally relevant teaching (e.g., brain focus on social and cross-cultural skills, pedagogical focus on teachers' learning, etc.). Finally, the literature review demonstrates that there are numerous strategies of using the STEAM educational framework to reinforce culturally relevant teaching (e.g., to design a culturally relevant program based on STEAM).
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Conference papers on the topic "Brain-based learning strategies"

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Malhotra, Radhika, Jasleen Saini, Barjinder Singh Saini, and Savita Gupta. "Improving Brain Tumor Segmentation with Data Augmentation Strategies." In International Conference on Women Researchers in Electronics and Computing. AIJR Publisher, 2021. http://dx.doi.org/10.21467/proceedings.114.2.

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In the past decade, there has been a remarkable evolution of convolutional neural networks (CNN) for biomedical image processing. These improvements are inculcated in the basic deep learning-based models for computer-aided detection and prognosis of various ailments. But implementation of these CNN based networks is highly dependent on large data in case of supervised learning processes. This is needed to tackle overfitting issues which is a major concern in supervised techniques. Overfitting refers to the phenomenon when a network starts learning specific patterns of the input such that it fits well on the training data but leads to poor generalization abilities on unseen data. The accessibility of enormous quantity of data limits the field of medical domain research. This paper focuses on utility of data augmentation (DA) techniques, which is a well-recognized solution to the problem of limited data. The experiments were performed on the Brain Tumor Segmentation (BraTS) dataset which is available online. The results signify that different DA approaches have upgraded the accuracies for segmenting brain tumor boundaries using CNN based model.
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Kim, Dongjae, and Sang Wan Lee. "Model-Based BCI: A Novel Brain-Computer Interface Framework for Reading Out Learning Strategies Underlying Choices." In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2018. http://dx.doi.org/10.1109/smc.2018.00091.

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Jiao, Zhicheng, Haoxuan You, Fan Yang, Xin Li, Han Zhang, and Dinggang Shen. "Decoding EEG by Visual-guided Deep Neural Networks." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/192.

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Decoding visual stimuli from brain activities is an interdisciplinary study of neuroscience and computer vision. With the emerging of Human-AI Collaboration, Human-Computer Interaction, and the development of advanced machine learning models, brain decoding based on deep learning attracts more attention. Electroencephalogram (EEG) is a widely used neurophysiology tool. Inspired by the success of deep learning on image representation and neural decoding, we proposed a visual-guided EEG decoding method that contains a decoding stage and a generation stage. In the classification stage, we designed a visual-guided convolutional neural network (CNN) to obtain more discriminative representations from EEG, which are applied to achieve the classification results. In the generation stage, the visual-guided EEG features are input to our improved deep generative model with a visual consistence module to generate corresponding visual stimuli. With the help of our visual-guided strategies, the proposed method outperforms traditional machine learning methods and deep learning models in the EEG decoding task.
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Kim, Dongjae, Charles Weston, and Sang Wan Lee. "EEG-based classification of learning strategies : Model-based and model-free reinforcement learning." In 2018 6th International Conference on Brain-Computer Interface (BCI). IEEE, 2018. http://dx.doi.org/10.1109/iww-bci.2018.8311522.

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Enikov, Eniko T., Juan-Antonio Escareno, and Micky Rakotondrabe. "Image Schema Based Landing and Navigation for Rotorcraft MAV-s." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-51450.

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To date, most autonomous micro air vehicles (MAV-s) operate in a controlled environment, where the location of and attitude of the aircraft are measured with an infrared (IR) tracking systems. If MAV-s are to ever exit the lab, their flight control needs to become autonomous and based on on-board image and attitude sensors. To address this need, several groups are developing monocular and binocular image based navigation systems. One of the challenges of these systems is the need for exact calibration in order to determine the vehicle’s position and attitude through the solution of an inverse problem. Body schemas are a biologically-inspired approach, emulating the plasticity of the animal brain, which allows it to learn non-linear mappings between the body configurations, i.e. its generalized coordinates and the resulting sensory outputs. The advantages of body schemas has long been recognized in the cognitive robotic literature and resulting studies on human-robot interactions based on artificial neural networks, however little effort has been made so far to develop avian-inspired flight control strategies utilizing body and image schemas. This paper presents a numerical experiment of controlling the trajectory of a miniature rotorcraft during landing maneuvers suing the notion of body and image schemas. More specifically, we demonstrate how trajectory planning can be executed in the image space using gradient-based maximum seeking algorithm of a pseudo-potential. It is demonstrated that a neural-gas type artificial neural network (ANN), trained through Hebbian-type learning algorithm, can be effective in learning a mapping between the rotorcraft’s position/attitude and the output of its vision sensors. Numerical simulation of the landing performance, including resulting landing errors are presented using an experimentally validated rotorcraft model.
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Khan, Hassan, and Clifford Louis. "An Artificial Intelligence Neural Networks Driven Approach to Forecast Production in Unconventional Reservoirs – Comparative Analysis with Decline Curve." In International Petroleum Technology Conference. IPTC, 2021. http://dx.doi.org/10.2523/iptc-21350-ms.

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Abstract Subsurface engineers pivot on surveillance of reservoir performance for future production rates and plan the optimization strategies at earliest. There are some techniques preferred for unconventional reservoirs such as numerical simulation and decline curve analysis (DCA) for production forecasting, but the uncertainty of uneconomical well test data often occurs in unconventional resources. Moreover, reservoir engineers can also hit a tailback in optimizing and tuning the model. Further, for DCA this approach is only appropriate for well/reservoir that are under boundary dominant flow regime, whereas fracture dominant flow regime is often observed for a longer period in unconventional hydraulically fractured reservoirs. Therefore, to resolve this issue, oil & gas industry (O&G) can adopt AI (Artificial Intelligence) based Algorithms for production forecasting. This paper presents a data-driven algorithm, known as Artificial Neural Networks (ANNs), along with time series forecasting that is a well-known statistical technique. Machine learning model trained by a past well performance data such as tubing head pressure (THP), flowing bottom-hole pressure can predict future production rates. This can be an efficient technique for subsurface engineers to monitor and optimize well performance. Time series neural networks were used for training the model at top and bottom node of the well with variating pressures in the past. After training and validation, the model predicted a target parameter that was gas rate. ANNs are inspired by biological neurons that are present in human brain, a powerful computing tool to make decisions after fueling itself with data. Moreover, prediction (t+1) nonlinear automated regression is preferred for accurate step ahead. Production rates and constraints of unconventional reservoirs were used to train the model. In our results, the NN based model gave the co-efficient of determination (R2) of 0.996 that shows nearly an exact precision. Furthermore, the values generated from NN Model and Arp's decline curve calculations were plotted for validation and it turned out that ANN can accurately predict the parameters. The Neural Network model is a novel approach for production forecasting, of unconventional reservoirs and help engineers in corporate decision making. This approach can mitigate the need of uneconomical well test operations and further provide confidence to production engineers in terms of data and result expectations.
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