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Federica Picasso; Javiera Atenas; Leo Havemann; Anna Serbati – Open Praxis, 2024
The development of critical data and artificial intelligence (AI) literacy has become a key focus in current discussions in Higher Education, thus it is necessary to develop and advance capacity building, reflectiveness and awareness across disciplines to critically address the possibilities and challenges presented by data and AI. In this paper,…
Descriptors: Undergraduate Students, College Faculty, Artificial Intelligence, Data Collection
Corinne Thatcher Day – Mathematics Teacher: Learning and Teaching PK-12, 2025
Since data collection technologies has become a part of daily life, measurement and data requirements now permeate many state mathematics standards, beginning as early as kindergarten and extending through high school. For example, the Standards for Mathematical Content, recommend that kindergarteners "describe and compare measurable…
Descriptors: Middle School Mathematics, Middle School Students, Middle School Teachers, High School Students
Hui, Bowen – International Journal of Information and Learning Technology, 2022
Purpose: The purpose of this work is to illustrate the processes involved in managing teams in order to assist designers and developers to build software that support teamwork. A deeper investigation into the role of team analytics is discussed in this article. Design/methodology/approach: Many researchers over the past several decades studied the…
Descriptors: Design, Guidelines, Research Needs, Teamwork
Gachago, Daniela; Livingston, Candice – Reading & Writing: Journal of the Reading Association of South Africa, 2020
Background: Digital storytelling (DST) has been embraced in classrooms around the world as a way to unpack issues of identity and positionality which are critical for any pedagogy concerned with social justice. However, adopting this process-orientated practice into higher education raises ethical concerns especially in relation to the normative…
Descriptors: Story Telling, Computer Uses in Education, Social Justice, Ethics
Sneider, Cary; Stephenson, Chris; Schafer, Bruce; Flick, Larry – Science Teacher, 2014
A "Framework for K-12 Science Education" identified eight practices as "essential elements of the K-12 science and engineering curriculum" (NRC 2012, p. 49). Most of the practices, such as Developing and Using Models, Planning and Carrying Out Investigations, and Analyzing and Interpreting Data, are well known among science…
Descriptors: High School Students, Secondary School Science, Thinking Skills, Computation
Problem Analysis: Examining the Selection and Evaluation of Data during Problem-Solving Consultation
Newell, Markeda L.; Newell, Terrance S. – Psychology in the Schools, 2011
The purpose of this study was to analyze how school psychologists engaged in problem analysis during problem-solving consultation. Five aspects of the problem analysis process were examined: 1) the types of questions participants asked during problem identification, 2) the types of data participants requested, 3) the frequency of requests for each…
Descriptors: School Psychologists, Identification, Problem Solving, Simulated Environment
Interactive Computer Based Assessment Tasks: How Problem-Solving Process Data Can Inform Instruction
Zoanetti, Nathan – Australasian Journal of Educational Technology, 2010
This article presents key steps in the design and analysis of a computer based problem-solving assessment featuring interactive tasks. The purpose of the assessment is to support targeted instruction for students by diagnosing strengths and weaknesses at different stages of problem-solving. The first focus of this article is the task piloting…
Descriptors: Computer Assisted Testing, Computer Uses in Education, Problem Solving, Evaluation Methods

Ainley, Janet; Nardi, Elena; Pratt, Dave – International Journal of Computers for Mathematical Learning, 2000
Describes research using a pedagogic strategy developed during an exploratory work called Active Graphing in which access to spreadsheets allows graphs to be used as analytic tools within practical experiments. Identifies aspects of student interaction with the experiment itself, the data collected and the graphs, and traces the emergence of…
Descriptors: Computer Uses in Education, Data Interpretation, Elementary Education, Graphs
Ubuz, Behiye – International Journal of Mathematical Education in Science and Technology, 2007
This present study investigated engineering students' conceptions and misconceptions related to derivative, particularly interpreting the graph of a function and constructing its derivative graph. Participants were 147 first year engineering students from four universities enrolled in first year undergraduate calculus courses with or without the…
Descriptors: Misconceptions, Mathematical Concepts, Engineering, Diagnostic Tests

Brewer, Steven D.; Hoogendky, Tom; Hoagland, Donald B. – Journal of Computing in Higher Education, 2003
Found that in an introductory biology course at the University of Massachusetts Amherst, adoption of the Data Aggregation Project (free software that allows students in a course to aggregate a large body of data for some particular problem) resulted in an increase in the number of data points students analyzed per semester by a factor of almost…
Descriptors: Computer Software, Computer Uses in Education, Data Collection, Data Interpretation

Menges, Robert – New Directions for Teaching and Learning, 2000
Menges identifies four areas of educational research in which data is substantial but much less useful than it could be: faculty behaviors and intentions; technology-mediated instruction; effective evaluative decisions and context-specific research. He suggests some directions for future research. (JM)
Descriptors: Computer Uses in Education, Data Interpretation, Educational Research, Educational Technology
Ozkan, Betul C.; McKenzie, Barbara K. – Online Submission, 2006
This paper explores a new approach to the evaluation of educational technologies by using Eisner's connoisseurship model. This model has two essential features in program evaluation: holistic approach to the analysis and interpretation of data and multiple perspectives in the evaluative tasks (Eisner, 1998). Using Eisner's model, the key…
Descriptors: Program Evaluation, Holistic Approach, Alternative Assessment, Educational Technology

Soares, Allan; Creevy, Steven – School Science Review, 1995
Presents a distillation experiment that uses temperature sensors connected to a computer in place of thermometers, and enables the whole class to view the data on a monitor and interpret and discuss the data in real time. (JRH)
Descriptors: Chemistry, Computer Interfaces, Computer Uses in Education, Data Interpretation

Sumrall, William J.; Halpin, Regina F. – Science Scope, 2000
Discusses teaching display and presentation skills by incorporating it into an interdisciplinary computer, math, and science lesson on graphing and collecting data which reinforces problem-solving skills and develops students' abilities to graph and interpret data. (ASK)
Descriptors: Computer Uses in Education, Data Collection, Data Interpretation, Data Processing

Corbeil, Pierre – History Computer Review, 1999
Considers what computers contribute to the work of historians, and of history teachers, that is specific to the nature of computers and cannot be accomplished by other tools available to historians today. Suggests that simulation games and databases be used to reduce the historian's unspoken biases when examining the conditions of historical…
Descriptors: Computer Attitudes, Computer Games, Computer Simulation, Computer Uses in Education