Types of Manuscripts
TISE welcomes papers that advance our understanding of how to better teach statistics with technology or how to better teach technology to future data scientists. Manuscripts may focus on any level of education, including graduate and post-graduate education, professional development, college, and K-12.
There are three categories of manuscripts of interest to TISE: Research papers, Position papers, and technology innovations. Authors are requested to identify, in their cover letter, their submission as one of the following types.
Research Papers may be empirical studies or conceptual/theoretical
articles. Empirical studies might contribute to a theory of learning or a
design of technology; or address the effectiveness of a particular technological tool
or design feature for teaching or learning statistics. Empirical studies use
appropriate, well-documented research methods and data analyses (whether qualitative
or quantitative) that support sound conclusions. An investigation of whether
alternative methods of teaching of statistical tools lead to better results than
another such method without a connection to theory and/or previous research would not
generally be acceptable. Papers should include a discussion of the broad impact of the
research. Quantitative measurements of student outcomes should be aligned with the
theoretical foundations of the study and evidence given as to their reliability and
validity. Student performance on a final exam or end of course grade would not
generally pass these tests.
Conceptual studies provide a new perspective on a problem, technology, or body of work. Manuscripts should provide evidence that the study is based on and situated in prior work, include a discussion of the broader impact of the study, use sound argumentation and reasoning, and if appropriate, provide empirical examples to illustrate. Conceptual studies might, for example, develop a critical context for evaluating software, summarize recent innovations in the research literature that are under-appreciated or poorly understood, or point out critical gaps in the research literature and propose approaches for filling these gaps.
- Position Papers describe a timely issue in learning or teaching statistics with or about technology and propose novel solutions or perspectives. Issues discussed should be of interest to a broad audience. Ideally, manuscripts will include a discussion of and comparison with alternative solutions and propose a solution that is feasible in a variety of settings. For example, a position paper might argue that changes in technology require a change in the curriculum, either to remove or add topics. Or one might argue that new technology allows a new and better approach to teaching fundamental concepts. Position papers are likely to be published with discussion.
Technology Innovations are of two types: discussions of new
technology created by the author(s) or case studies of innovative uses of existing
technology. New technologies should solve educational problems, provide
infrastructure to assist statistics educators, or provide infrastructure to assist
developers of statistics education technology. New Technology manuscripts should
provide (at a minimum) a pedagogical context for the technology that includes a
discussion of how the technology is meant to be used, who the intended users are, and
what skills or concepts it is meant to help students learn. Manuscripts should provide
a high-level description of the technology that includes discussing features of the
design. Manuscripts must include a comparison and contrast with competing
technologies, as appropriate. Authors should explain why the technology is innovative.
Examples of New Technologies might include, but certainly not be limited to, web-based
statistical software, applets designed to teach statistical concepts, or technology
that harvests data for classroom use.
Technology Case Studies are descriptions of particular innovative uses of existing technology to improve statistics education or are descriptions of methods for teaching the use of technology to solve problems of general statistical interest. Technology case studies should be feasible in a variety of settings, and authors should discuss implementation and access issues (e.g. cost, maintenance). Authors must provide a pedagogical context that includes a description of the problem solved by the use of technology and, more particularly, a description of the setting in which the authors implemented the technology. Examples might include descriptions of using data collection problems to collect "live" data, an example of using XML for data exchange, or demonstrations of teaching technologies that allow students to access unusual or complex data formats.