About this paper

Appears in:
Page: 3370 (abstract only)
Publication year: 2015
ISBN: 978-84-606-8243-1
ISSN: 2340-1117

Conference name: 7th International Conference on Education and New Learning Technologies
Dates: 6-8 July, 2015
Location: Barcelona, Spain

MODELING OF CAUSAL AND TEMPORAL RELATIONSHIPS TO AID TEACHING ANALYTICAL AND PROBLEM SOLVING SKILLS IN K-12

J. Bergandy

University of Massachusetts Dartmouth (UNITED STATES)
This paper describes one of the key facets of a large multi-stage project addressing deficiencies in analytical and problem solving skills of K-12 students. The process of solving a problem requires the capture of all relevant facts and the identification of all relationships between these facts valid in the context of the solved problem. For large problems, this process is performed in an iterative manner and results in a very large number of facts and their mutual relationships. The recording and effective manipulation of many facts and relationships requires sophisticated graphics-based tools. Such tools do not only address the challenge of navigation thorough vast amounts of data but also effectively facilitate verification and validation of this data.

The approach of our project is to use Unified Modeling Language (UML) and UML modeling software tools to aid in the teaching of analytical and problem solving skills in K-12 classrooms. UML is a standardized graphical modeling language used for the design and analysis of software systems. The driving forces behind the idea of using UML are its intuitive nature, low learning curve for students, graphical mode of representation, and easy-to-use tools.

The project started with a study of teachers’ sentiments, preparation, and motivation for the proposed approach. It continued with work on using this methodology for teaching natural sciences and social sciences. We developed guidelines and materials for the teachers that were carefully mapped into the Massachusetts Curriculum Standards. One phase of the project specifically focused on using UML in the design and execution of scientific experiments with an objective to not only aid student learning but also student safety.

This paper looks at modeling causal and temporal relationships in a way that is domain/subject independent. It provides domain-specific examples only to illustrate the concepts. The behavior of any system/entity can be modeled in terms of its states and its activities performed in reaction to conditions and events. Examples of specific entities include individuals (Churchill, John – peer students), groups of people (society/nation, soccer team), devices (computer, car), and processes (World War II, chemical reaction, bank transaction). The behavior of an entity causes events and changing conditions that impact other entities. This general approach, when applied to solving a specific problem, requires identification of specific entities, their activities, and relevant conditions. The tools we are using in this process are UML activity diagrams and UML state diagrams. Our approach allows students to capture not only conditional activities but also to explore parallelism (activities that overlap in time). It scales easily to modeling and analysis of alternative or hypothetical scenarios.
@InProceedings{BERGANDY2015MOD,
author = {Bergandy, J.},
title = {MODELING OF CAUSAL AND TEMPORAL RELATIONSHIPS TO AID TEACHING ANALYTICAL AND PROBLEM SOLVING SKILLS IN K-12},
series = {7th International Conference on Education and New Learning Technologies},
booktitle = {EDULEARN15 Proceedings},
isbn = {978-84-606-8243-1},
issn = {2340-1117},
publisher = {IATED},
location = {Barcelona, Spain},
month = {6-8 July, 2015},
year = {2015},
pages = {3370}}
TY - CONF
AU - J. Bergandy
TI - MODELING OF CAUSAL AND TEMPORAL RELATIONSHIPS TO AID TEACHING ANALYTICAL AND PROBLEM SOLVING SKILLS IN K-12
SN - 978-84-606-8243-1/2340-1117
PY - 2015
Y1 - 6-8 July, 2015
CI - Barcelona, Spain
JO - 7th International Conference on Education and New Learning Technologies
JA - EDULEARN15 Proceedings
SP - 3370
EP - 3370
ER -
J. Bergandy (2015) MODELING OF CAUSAL AND TEMPORAL RELATIONSHIPS TO AID TEACHING ANALYTICAL AND PROBLEM SOLVING SKILLS IN K-12, EDULEARN15 Proceedings, p. 3370.
User:
Pass: