Digital technology in mathematics education: Why it works (or doesn't)

The integration of digital technology confronts teachers, educators and researchers with many questions. What is the potential of ICT for learning and teaching, and which factors are decisive in making it work in the mathematics classroom? To investigate these questions, six cases from leading studies in the field are described, and decisive success factors are identified. This leads to the conclusion that crucial factors for the success of digital technology in mathematics education include the design of the digital tool and corresponding tasks exploiting the tool's pedagogical potential, the role of the teacher and the educational context

Class tournament as an assessment method in physics courses : a pilot study

Testing knowledge is an integral part of a summative assessment at schools. It can be performed in many different ways. In this study we propose assessment of physics knowledge by using a class tournament approach. Prior to a statistical analysis of the results obtained over a tournament organized in one of Polish high schools, all its specifics are discussed at length, including the types of questions assigned, as well as additional self- and peer-evaluation questionnaires, constituting an integral part of the tournament. The impact of the tournament upon student improvement is examined by confronting the results of a post-test with pre-tournament students’ achievements reflected in scores earned in former, tests written by the students in experimental group and their colleagues from control group. We also present some of students’ and teachers’ feedback on the idea of a tournament as a tool of assessment. Both the analysis of the tournament results and the students’ and teachers’ opinions point to at least several benefits of our approach

Logistics of Mathematical Modeling-Focused Projects

This article addresses the logistics of implementing projects in an undergraduate mathematics class and is intended both for new instructors and for instructors who have had negative experiences implementing projects in the past. Project implementation is given for both lower and upper division mathematics courses with an emphasis on mathematical modeling and data collection. Projects provide tangible connections to course content which can motivate students to learn at a deeper level. Logistical pitfalls and insights are highlighted as well as descriptions of several key implementation resources. Effective assessment tools, which allowed me to smoothly adjust to student feedback, are demonstrated for a sample class. As I smoothed the transition into each project and guided students through the use of the technology, their negative feedback on projects decreased and more students noted how the projects had enhanced their understanding of the course topics. Best practices learned over the years are given along with project summaries and sample topics. These projects were implemented at a small liberal arts university, but advice is given to extend them to larger classes for broader use.Comment: 27 pages, no figures, 1 tabl

Using Scratch to Teach Undergraduate Students' Skills on Artificial Intelligence

This paper presents a educational workshop in Scratch that is proposed for the active participation of undergraduate students in contexts of Artificial Intelligence. The main objective of the activity is to demystify the complexity of Artificial Intelligence and its algorithms. For this purpose, students must realize simple exercises of clustering and two neural networks, in Scratch. The detailed methodology to get that is presented in the article.Comment: 6 pages, 7 figures, workshop presentatio

The technological mediation of mathematics and its learning

This paper examines the extent to which mathematical knowledge, and its related pedagogy, is inextricably linked to the tools – physical, virtual, cultural – in which it is expressed. Our goal is to focus on a few exemplars of computational tools, and to describe with some illustrative examples, how mathematical meanings are shaped by their use. We begin with an appraisal of the role of digital technologies, and our rationale for focusing on them. We present four categories of digital tool-use that distinguish their differing potential to shape mathematical cognition. The four categories are: i. dynamic and graphical tools, ii. tools that outsource processing power, iii. new representational infrastructures, and iv. the implications of highbandwidth connectivity on the nature of mathematics activity. In conclusion, we draw out the implications of this analysis for mathematical epistemology and the mathematical meanings students develop. We also underline the central importance of design, both of the tools themselves and the activities in which they are embedded

What\u27s Wrong With American Secondary Schools: Can State and Federal Governments Fix it?

[Excerpt] The poor performance of American students is sometimes blamed on the nation\u27s diversity . Many affluent parents apparently believe that their children are doing acceptably by international standards. This is not the case. In Stevenson, Lee and Stigler\u27s (1986) study of 5th grade math achievement, the best of the 20 classrooms sampled in Minneapolis was outstripped by every single classroom studied in Sendai, Japan and by 19 of the 20 classrooms studied in Taipeh, Taiwan. The nation\u27s top high school students rank far behind much less elite samples of students in other countries. In mathematics the gap between Japanese and Finnish high school seniors and their white American counterparts is about twice the size of the two to three grade level equivalent gap between blacks and whites in the US (NAEP 1988b; IAEEA 1987). The learning deficit is pervasive

Enriching accounts of computer‐supported collaboration by using video data

This paper will discuss the approach to the evaluation of computer‐supported collaborative learning developed in our group over the past ten years. This approach depends on the collection of video data to allow the analysis of key features of problem‐solving behaviour within groups of students working on collaborative learning tasks. Our theoretical framework derives from two sources‐ the CIAOl framework for evaluating examples of CAL and an analysis of appropriate methods of evaluating computer‐supported collaboration. Our work in this area has been supported by developing the data capture facilities for the CALRG (Computers and Learning Research Group) at the Open University. We will draw on a number of studies to illustrate this approach and will present a brief case study from work done on a computer‐supported learning environment for statistics where we use video records of video‐mediated collaboration. This case study gives an example of the rich data that can be collected using video recording and analysed to increase understanding of computer‐supported collaboration