Using ICT to support constructive learning

Information and Communication Technology (ICT) tools and Assistive Technologies (AT) can support people with Down Syndrome (PDS) and Intellectual Disabilities (PID) in increasing their self-confidence and independence, enhancing skills, and competences, participating in leisure activities. For families of PDS/PID, professionals, non-formal caregivers and volunteers, the challenge is to appreciate the benefits of ICT Tools in promoting inclusion. The aim of this study is to present the interdisciplinary and multidimensional scope of the DS Leisure project aiming at promoting the inclusion of PDS/PID through innovative ICT tools and their participation in inclusive leisure activities. Particularly, 24 individuals were asked to assess the global satisfaction and performance of PDS/PID, as well as the exploitation of ICT tools. Findings suggested that PDS/PID specific social, decision-making, and communication skills were significantly improved after their participation in the Experiential Activity and the e-Training platform was positively rated and considered a constructive learning experience.

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Education for Social Change: The Case of Teacher Education in Wales

Sustainability ◽

10.3390/su13158574 ◽

2021 ◽

Vol 13 (15) ◽

pp. 8574

Author(s):

Rebecca Weicht ◽

Svanborg R. Jónsdóttir

Keyword(s):

Teacher Education ◽

Social Change ◽

Teacher Educators ◽

Entrepreneurial Education ◽

Constructive Learning ◽

Study Approach ◽

The University ◽

Action Competence ◽

Shed Light

Entrepreneurial education offers valuable opportunities for teachers to foster and enhance creativity and action competence, which are also important for sustainability education. The University of Wales Trinity Saint David (UWTSD) is a leader in the development of entrepreneurial education in teacher education both in Wales and internationally. The objective of this article is to shed light on how an entrepreneurial education approach can help foster social change. The aim of this study is to learn from teacher educators at UWTSD about how they support creativity, innovation, and an enterprising mindset in their learners. A case study approach is applied. By analysing documentary evidence such as module and assignment handbooks, we explore how teacher educators at UWTSD deliver entrepreneurial education for social change. Our findings indicate that UWTSD’s development of entrepreneurial education in teacher training has enabled constructive learning, cultivating creativity and action competence. We provide examples that display how the intentions of the Curriculum for Wales and entrepreneurial education approaches of the UWTSD emerge in practice. These examples show outcomes of the entrepreneurial projects that evince the enactment of social change. The findings also show that the educational policy of Wales supports entrepreneurial education throughout all levels of the educational system.

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LUVE: A Constructive Learning Approach for Working with Parents

Families in Society The Journal of Contemporary Social Services ◽

10.1606/1044-3894.22 ◽

2002 ◽

Vol 83 (3) ◽

pp. 275-284 ◽

Cited By ~ 1

Author(s):

Lucía Santelices Cuevas ◽

Verónica Astroza

Keyword(s):

Sex Education ◽

Teaching Strategy ◽

Active Role ◽

Descriptive Study ◽

Learning Approach ◽

Cross Sectional ◽

Constructive Learning ◽

Second Stage ◽

Teachers And Parents ◽

Two Stages

This study examines the application of a didactic teaching strategy called LUVE. Based on a constructivist learning approach, LUVE's purpose is to develop collaborative links between schools and parents, so that parents can improve their daily educational practices with their children and assume a more active role in their children's education. The project took place in Santiago, Chile, and was implemented in two stages. The first stage included a cross-sectional descriptive study with an experimental design, focusing on parents. The second stage involved teachers and parents who applied and carried out the LUVE strategy, The project's content focused on sex education, as this was the topic of interest to parents. The findings indicate that the strategy was a successful experience for the parents.

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Robot as an Constructive Learning Tool for Computer Programming: the Practices in Taiwan

2020 8th International Conference on Orange Technology (ICOT) ◽

10.1109/icot51877.2020.9468807 ◽

2020 ◽

Author(s):

Shih-Pang Tseng ◽

Jhing-Fa Wang

Keyword(s):

Computer Programming ◽

Learning Tool ◽

Constructive Learning

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Constructive Learning Theory: Exploring the Possibilities for this Interactive Teaching Learning Methods in Physiotherapy Education

Journal of Novel Physiotherapies ◽

10.4172/2165-7025.1000258 ◽

2015 ◽

Vol 05 (02) ◽

Author(s):

Swati Meshram

Keyword(s):

Learning Theory ◽

Learning Methods ◽

Interactive Teaching ◽

Constructive Learning ◽

Teaching Learning ◽

Physiotherapy Education

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Constructive Learning of Deep Neural Networks for Bigdata Analysis

International Journal of Computer Applications Technology and Research ◽

10.7753/ijcatr0912.1001 ◽

2020 ◽

Vol 9 (12) ◽

pp. 311-322

Author(s):

Soha Abd Mohamed El-Moamen ◽

Marghany Hassan Mohamed ◽

Mohammed F. Farghally

Keyword(s):

Neural Network ◽

Lung Cancer ◽

Binary Classification ◽

Network Models ◽

Classification Model ◽

Neural Network Models ◽

Constructive Learning ◽

The Neural Network ◽

Rapid Pace ◽

Better Than

The need for tracking and evaluation of patients in real-time has contributed to an increase in knowing people’s actions to enhance care facilities. Deep learning is good at both a rapid pace in collecting frameworks of big data healthcare and good predictions for detection the lung cancer early. In this paper, we proposed a constructive deep neural network with Apache Spark to classify images and levels of lung cancer. We developed a binary classification model using threshold technique classifying nodules to benign or malignant. At the proposed framework, the neural network models training, defined using the Keras API, is performed using BigDL in a distributed Spark clusters. The proposed algorithm has metrics AUC-0.9810, a misclassifying rate from which it has been shown that our suggested classifiers perform better than other classifiers.

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