So just what is conceptual understanding of mathematics?

2008 ◽  
Vol 8 (3) ◽  
pp. 2-6 ◽  
Author(s):  
Douglas Quinney
Keyword(s):  
Conceptual Understanding

Teaching Resilience to People With Visual Disabilities

2018 ◽  
Vol 5 (1) ◽  
pp. 36
Author(s):  
Inger Solange Maitta Rosado ◽  
Jenmer Maricela Pinargote Ortega ◽  
Eva Alcivar Medranda ◽  
Elisa Ximena Coello Basurto
Keyword(s):  
Visual Impairment ◽  
Conceptual Understanding ◽  
Conceptual Analysis ◽  
Psychological Support ◽  
Visual Disability ◽  
Visual Disabilities ◽  
The Subject ◽  
Technical University

The objective of the research is to develop resilience in people with visual disabilities at the Technical University of Manabí. The work offers a conceptual analysis on visual disability in students. It deals with what is related to the conceptual understanding of resilience, where several authors who have studied the subject are analyzed. The resilient capacity of students with visual impairment and the importance of psychological support is analyzed. The importance of the intervention in resilience is exposed, where the content of the Manual of Intervention in Resilience of Eugenio Saavedra 2011 is analyzed. The results of the measurement of resilience are shown in the students of the Technical University of Manabí who suffer from a visual disability and the situation that could be verified after applying the work of training in resilience to said personnel. Finally, the conclusions of the work are exposed, where the relevance of the study is demonstrated and a group of recommendations is made based on the importance of the results obtained in the research.

Conceptual understanding of Kshara Karma in Shalakya Tantra

2017 ◽  
Vol 2 (3) ◽  
Author(s):  
Mahantaswamy S. Chappanmath ◽  
Vinod M. Jadhav
Keyword(s):  
Conceptual Understanding ◽  
Surgical Procedures ◽  
Research Work ◽  
Effective Management ◽  
Optimum Result

Kshara Karma, Agni Karma is known as Anushastra Karmas. Popularly understood as Para surgical procedures. They are outstanding contributions of Acharya Shushruta. The surgical disorders are managed with these procedures with ease and comfort for both surgeon and patients. In Shalakya Tantra there is a need of adopting these procedures for effective management of disorders such as Upajihwa, Adhijihwa, Upakusha, Dantavaidharbha, three types of Rohini, Nasarsha, Karnarsha and Pakshmakopa. Kshara Karma said to be one among the Anushastra Karma explained by Acharya Shushruta which is not widely practised and popularised in Shalakya diseases. There is need of research work in this area to utilize Kshara Karma and give optimum result.

Synthesising Privacy by Design Knowledge Toward Explainable Internet of Things Application Designing in Healthcare

2021 ◽  
Vol 17 (2s) ◽  
pp. 1-29
Author(s):  
Lamya Alkhariji ◽  
Nada Alhirabi ◽  
Mansour Naser Alraja ◽  
Mahmoud Barhamgi ◽  
Omer Rana ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Conceptual Understanding ◽  
Knowledge Engineering ◽  
Privacy Preserving ◽  
Design Knowledge ◽  
Privacy By Design ◽  
Healthcare Applications ◽  
Software Developers ◽  
Healthcare Application ◽  
Application Design

Privacy by Design (PbD) is the most common approach followed by software developers who aim to reduce risks within their application designs, yet it remains commonplace for developers to retain little conceptual understanding of what is meant by privacy. A vision is to develop an intelligent privacy assistant to whom developers can easily ask questions to learn how to incorporate different privacy-preserving ideas into their IoT application designs. This article lays the foundations toward developing such a privacy assistant by synthesising existing PbD knowledge to elicit requirements. It is believed that such a privacy assistant should not just prescribe a list of privacy-preserving ideas that developers should incorporate into their design. Instead, it should explain how each prescribed idea helps to protect privacy in a given application design context—this approach is defined as “Explainable Privacy.” A total of 74 privacy patterns were analysed and reviewed using ten different PbD schemes to understand how each privacy pattern is built and how each helps to ensure privacy. Due to page limitations, we have presented a detailed analysis in Reference [3]. In addition, different real-world Internet of Things (IoT) use-cases, including a healthcare application, were used to demonstrate how each privacy pattern could be applied to a given application design. By doing so, several knowledge engineering requirements were identified that need to be considered when developing a privacy assistant. It was also found that, when compared to other IoT application domains, privacy patterns can significantly benefit healthcare applications. In conclusion, this article identifies the research challenges that must be addressed if one wishes to construct an intelligent privacy assistant that can truly augment software developers’ capabilities at the design phase.

The More, the Merrier? Roles of Device-Student Ratio in Collaborative Inquiries and Its Interactions With External Scripts and Task Complexity

2021 ◽  
pp. 073563312110107
Author(s):  
Cixiao Wang ◽  
Huixiao Le
Keyword(s):  
Conceptual Understanding ◽  
Repeated Measures ◽  
Task Complexity ◽  
Mainland China ◽  
Fifth Grade ◽  
Learning Context ◽  
Simple Task ◽  
Fifth Grade Students ◽  
Main Effect ◽  
The Relationship

In collaborative learning, the intuition “the more device, the merrier” is somehow widely acknowledged, but little research has investigated the relationship between device-student ratio and the learning outcome. This study aims to investigate not only the main effect of different device-student ratio, also to identify the moderators in the learning context including task complexity, external script availability and students’ familiarity to the collaboration settings. A three-round quasi-experiment was conducted in a primary school in mainland China, 130 fifth-grade students from four classes participated. Group worksheet including conceptual understanding and problem-solving tasks were used to collect participants’ inquiry performance. Repeated measures ANOVA was employed in data analysis. Findings indicate that 1:m device-student ratio could be beneficial, and external scripts, and prior collaboration experience could moderate such effect. The different effect of 1:m device-student ratio to 1:1 is only significant in the situation when students are faced with relatively simple task, and the effect size is larger when external script is present. When the task is more complicated, such effect of device-student ratio would only emerge after a period of collaboration. This finding challenged the intuition that one-to-one device-student ratio could be better. Related discussions and recommendations to teaching were made.

Sign in / Sign up

Export Citation Format

Share Document