634,659 research outputs found
Active Learning: An Integrative Learning Approach for Adult Learners
In order to appeal to adult learners, the Analytics in Medicine course utilizes active learning methodology to foster self-directed learning, critical thinking, communication skills, and acquisition of knowledge. The modified flipped classroom model requires weekly assigned reading and a written reflection exercise completed several days before face-to-face class time. The reflections are used to better inform course instructors regarding areas needing further explanation in person. In the weekly 2-hour class, students explore topics in-depth by incorporating active learning methods. Examples include think-pair-share or small group activities requiring movement, discussion, and reflection focusing on question prompts or application of principles (e.g., carousel method). The instructor continuously circulates to ensure student engagement and grasp of the material, allowing for areas of clarification to be immediately identified. Instructors often involve peers to coach one another as a method of continued active learning without going into “lecture mode.”https://digitalscholarship.unlv.edu/btp_expo/1092/thumbnail.jp
Personality and learning styles towards the practical-based approach
An enduring question for educational research is the result of individual deviations in the efficacy of learning. The individual learning differences that have been much explored relate to differences in personality, learning styles, strategies and conceptions of learning. This article studies the personality and the learning style profile exhibited by students in a practical based approach of vocational courses. The relationship between personality and learning styles among students was assessed as the students got along through the curriculum. The analysis show that students are more oriented towards an active learning mode in a practical-based approach. Given a specific instruction, some people will learn more effectively than others due to their individual personality and learning styles. This study will help a vocational instructor and advisors to understand their students and to design instruction that can benefit students to accomplish a respectable performance in their learning process
A Coverage Monitoring algorithm based on Learning Automata for Wireless Sensor Networks
To cover a set of targets with known locations within an area with limited or
prohibited ground access using a wireless sensor network, one approach is to
deploy the sensors remotely, from an aircraft. In this approach, the lack of
precise sensor placement is compensated by redundant de-ployment of sensor
nodes. This redundancy can also be used for extending the lifetime of the
network, if a proper scheduling mechanism is available for scheduling the
active and sleep times of sensor nodes in such a way that each node is in
active mode only if it is required to. In this pa-per, we propose an efficient
scheduling method based on learning automata and we called it LAML, in which
each node is equipped with a learning automaton, which helps the node to select
its proper state (active or sleep), at any given time. To study the performance
of the proposed method, computer simulations are conducted. Results of these
simulations show that the pro-posed scheduling method can better prolong the
lifetime of the network in comparison to similar existing method
Information-Theoretic Active Learning for Content-Based Image Retrieval
We propose Information-Theoretic Active Learning (ITAL), a novel batch-mode
active learning method for binary classification, and apply it for acquiring
meaningful user feedback in the context of content-based image retrieval.
Instead of combining different heuristics such as uncertainty, diversity, or
density, our method is based on maximizing the mutual information between the
predicted relevance of the images and the expected user feedback regarding the
selected batch. We propose suitable approximations to this computationally
demanding problem and also integrate an explicit model of user behavior that
accounts for possible incorrect labels and unnameable instances. Furthermore,
our approach does not only take the structure of the data but also the expected
model output change caused by the user feedback into account. In contrast to
other methods, ITAL turns out to be highly flexible and provides
state-of-the-art performance across various datasets, such as MIRFLICKR and
ImageNet.Comment: GCPR 2018 paper (14 pages text + 2 pages references + 6 pages
appendix
Strategi Penguatan Pendidikan Karakter Dalam Pembelajaran Berbasis Moda Daring
Character education is very important for individuals to be instilled early on. It is the accuracy of character education that will determine the results. In online mode-based learning, distance learning must have various learning strategies and appropriate reinforcement that can maintain student character in following the learning process. This study aims to determine the strategies used in strengthening character education in online mode-based learning. This research uses a descriptive qualitative approach. Data collection techniques through observation and literature study. The results of this study indicate that the strategy of strengthening character education in online mode-based learning is a series of activities that need to be carried out in improving the quality or quality of education. In improving the quality of education, it must be done with a strategy of choosing a good teaching method that is relevant to the current situation. The strategy designed is made with something active, innovative, creative, and fun and motivates students to stay active in online mode-based learning. Strategies like this can also help students from their psychological conditions because students feel bored with online learning at home with repeated and continuous time
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