Experiential learning in building physics: The icebox challenge

2021 ◽  
pp. 174425912110179
Author(s):  
Robert S McLeod ◽  
Christina J Hopfe
Keyword(s):  
Energy Transfer ◽  
Deep Learning ◽  
Experiential Learning ◽  
Learning Cycle ◽  
Learning Activity ◽  
Analysis Process ◽  
Building Physics ◽  
Transfer Principles ◽  
Physics Problems

This pedagogical note presents a novel learning activity (the icebox challenge) that was designed to facilitate deep learning of building physics energy transfer principles through a planning, prediction and analysis process following the Kolb learning cycle. The success of this strategy was evidenced by students relating and collating their knowledge and theoretical ideas and applying them to successfully solve a series of complex and inter-related practical building physics problems.

scholarly journals Applying Experiential Learning Kolb’s Model into Disigning “Experiential Learning Cycle” in Teaching Biology in General School

2017 ◽  
Vol 33 (3) ◽  
Author(s):  
Tran Thi Gai
Keyword(s):  
Experiential Learning ◽  
Learning Style ◽  
Learning Activities ◽  
Learning Cycle ◽  
Learning Activity ◽  
Learning Tasks ◽  
Concrete Experience ◽  
Teacher Needs ◽  
Teaching Biology ◽  
General School

The paper presents how to apply David Kolb's experiential learning cycle into the designing experiential learning activities for students in teaching Biology. Based on the objective, content, and learning style of the student, the teacher designs learning tasks at four stages of the experiential cycle: concrete experience, reflective observation, abstract conceptualisation and active experimentation. Each stage of the experiential learning cycle can be taken many forms of learning activity, so the teacher needs to select the appropriate types of activity for each stage and put the stages into a closed cycle to organize the learning. The article also provides an illustrative example of applying  experiential cycle in designing learning activities in teaching Biology in general school.

scholarly journals Digital historiefortelling i arbeidsplassbasert barnehagelærerutdanning – arbeidsmåte for individuell og kollektiv læring

2016 ◽  
Vol 12 ◽  
Author(s):  
Kristin Holte HAUG
Keyword(s):  
Higher Education ◽  
Experiential Learning ◽  
Creative Process ◽  
Personal Narratives ◽  
Learning Processes ◽  
Kindergarten Teacher ◽  
Learning Cycle ◽  
Research Focus ◽  
Teacher Students ◽  
Beneficial Approach

Abstract: This article presents Norwegian Kindergarten Teacher students’ and Kindergarten staff’s use of Digital Storytelling (DS), a tool for reflection and learning in higher education. The field of DS’ research focus on the use of personal narratives in the learning process, multimedia, and the creative process in developing identity and voice in a social context: the Story Circle. The frame is Workplace-based Kindergarten Teacher Education. The article is based on a case: student Yvonne’s work with DS in her kindergarten. Data is collected through observation and analyzed in light of theories on learning in practice, concretized to Kolb's experiential learning cycle. Results indicate that DS is a beneficial approach for facilitating both individual and collective reflection. A significant condition is that kindergarten staff participates in students' learning processes. Sammendrag: Artikkelen tar for seg barnehagelærerstudenters og barnehageansattes bruk av digital historiefortelling (DH), som er en arbeidsmåte for refleksjon og læring i høyere utdanning. DH kjennetegnes ved: fortellingens betydningen for læring i forhold til tradisjonell sakprosa, den multimodale dimensjonen og den kreative prosessen hvor fortellingen blir til i en sosial kontekst: fortellersirkelen. Rammen er Arbeidsplassbasert barnehagelærerutdanning. Artikkelen baseres på et case: studenten Yvonnes arbeid med DH i egen barnehage. Data er innhentet gjennom observasjon og fortolkes i lys av teorier om læring i praksis, konkretisert til Kolbs erfaringslæringsmodell. Jeg viser at DH tilrettelegger for individuell og kollektiv refleksjon for både studenter og barnehageansatte. Forutsetningen er at ansatte gis muligheter til å delta i studentenes læringsprosesser.

scholarly journals Sentiment Analysis using various Machine Learning and Deep Learning Techniques

2021 ◽  
pp. 385-394
Author(s):  
V Umarani ◽  
A Julian ◽  
J Deepa
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Sentiment Analysis ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Analysis Process ◽  
Learning Techniques

Sentiment analysis has gained a lot of attention from researchers in the last year because it has been widely applied to a variety of application domains such as business, government, education, sports, tourism, biomedicine, and telecommunication services. Sentiment analysis is an automated computational method for studying or evaluating sentiments, feelings, and emotions expressed as comments, feedbacks, or critiques. The sentiment analysis process can be automated using machine learning techniques, which analyses text patterns faster. The supervised machine learning technique is the most used mechanism for sentiment analysis. The proposed work discusses the flow of sentiment analysis process and investigates the common supervised machine learning techniques such as multinomial naive bayes, Bernoulli naive bayes, logistic regression, support vector machine, random forest, K-nearest neighbor, decision tree, and deep learning techniques such as Long Short-Term Memory and Convolution Neural Network. The work examines such learning methods using standard data set and the experimental results of sentiment analysis demonstrate the performance of various classifiers taken in terms of the precision, recall, F1-score, RoC-Curve, accuracy, running time and k fold cross validation and helps in appreciating the novelty of the several deep learning techniques and also giving the user an overview of choosing the right technique for their application.

scholarly journals OUTCOME BASED LEARNING: THE EFFECT OF EXPERIENTIAL LEARNING ACTIVITY ON DEEP CONCEPTUAL UNDERSTANDING

2021 ◽  
Vol 9 (6) ◽  
pp. 20-29
Author(s):  
Prashant Thote ◽  
Gowri S
Keyword(s):  
Experiential Learning ◽  
Conceptual Understanding ◽  
Learning Activities ◽  
Learning Activity ◽  
Control Group ◽  
Teaching Model ◽  
Study Group ◽  
Post Test ◽  
The Mean ◽  
Understanding Of Science

The aim of the present study is to investigate the effect of experiential learning activity in deep conceptual understanding of science in comparison with conventional teaching model. In the present experiment quasi experimental and post-test research design is implemented. Totally 80 students participate in the study: 40 girls and 40 boys. The sample is categorized into two: study and the control group. Each group consists of 40 students: 20 boys and 20 girls. The study group is taught “Gases Law” by using experiential learning activities and the control is taught by using the conventional method. Data is collected by using a questionnaire and it consists of 20 multiple choice questions. The collected data is analyzed by using descriptive statistics. The examination of the data illustrates that there is no noteworthy difference in the mean score between the study group and the control group. Independent ‘t-test’ is applied to compare the student’s achievement in post-test. The mean score of the study group, who are exposed to the experiential learning activities, in Science Achievement post-test is 17.35. It is higher than that of (t=6.65; p>0.01) the learners in the control group. The mean of the control group is 14.45. Therefore, it is concluded that the experiential learning activities as a teaching model enhances the deep conceptual understanding of science.

An Experiential Education Approach to Teaching the Mind-Body Problem

2021 ◽  
Vol 44 (1) ◽  
pp. 11-27
Author(s):  
Alexandru Manafu ◽  
Keyword(s):  
Experiential Learning ◽  
Experiential Education ◽  
Body Problem ◽  
Learning Activity ◽  
Experiential Learning Theory ◽  
Olfactory Experience ◽  
Length Width ◽  
Approach To Teaching ◽  
Mind Body Problem ◽  
The Mind

This article shows how the mind-body problem can be taught effectively via an experiential learning activity involving a couple of classroom props: a brick and a jar of ground coffee. By experiencing the physical properties of the brick (shape, weight, length, width) and contrasting them with the olfactory experience of coffee (seemingly dimensionless, weightless, etc.), students are introduced in a vivid way to the well-known difficulty of explaining the mental in physical terms. A brief overview of experiential learning theory and its connection to philosophy is also provided.

BEAN BAGS: AN EXPERIENTIAL LEARNING ACTIVITY FOR QUALITY CONTROL

2017 ◽  
Author(s):  
Angel Peiro-Signes ◽  
María del Val Segarra-Oña ◽  
Oscar Trull-Domínguez ◽  
Maria de Miguel-Molina
Keyword(s):  
Quality Control ◽  
Experiential Learning ◽  
Learning Activity
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