A Simple MVC-Framework for Local Management of Online Course Material

Research on E-Learning and ICT in Education

2018

Self Cite

Students' knowledge of inferential statistics is lacking in many Computer Science study programs. Yet, the needs for inferential statistic skills have emerged with new fields of study such as human-computer interaction involving observation of human activity. This paper presents experiences teaching inferential statistics to undergraduate computer science students with a focus on the actual goals of the investigations and not the mechanisms and mathematics of statistics. The teaching framework involves teaching statistics as a set of systematic black-box tools.

Section: Statistics Softwarementioning

confidence: 99%

Hostage of the Software: Experiences in Teaching Inferential Statistics to Undergraduate Human-Computer Interaction Students and a Survey of the Literature

Research on E-Learning and ICT in Education

2018

Self Cite

“…It is similar to the concepts of a regular spreadsheet such as Excel or the grid editor used in SPSS. The spreadsheet is a versatile and widely understood data entry tool [108]. However, the proposed observation editor distinguishes itself from the traditional spreadsheet in several ways.…”

Section: Observations Editormentioning

confidence: 99%

Towards a Framework for the Design of Quantitative Experiments: Human-Computer Interaction and Accessibility Research

Universal Access in Human-Computer Interaction. Methods, Technologies, and Users

Médola

2018

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Many students and researchers struggle with the design and analysis of empirical experiments. Such issue may be caused by lack of knowledge about inferential statistics and suitable software tools. Often, students and researchers conduct experiments without having a complete plan for the entire lifecycle of the process. Difficulties associated with the statistical analysis are often ignored. Consequently, one may end up with data that cannot be easily analyzed. This paper discusses the concept sketch of a framework that intends to help students and researchers to design correct empirical experiments by making sound design decisions early in the research process. The framework consists of an IDE, i.e., Integrated (statistical experiment) Development Environment. This IDE helps the user structures an experiment by giving continuous feedback drawing the experimenter's attention towards potential problems. The output of the IDE is an experimental structure and data format that can be imported to common statistical packages such as JASP in addition to providing guidance about what tests to use.

“…An IDE revolves around a code editor with syntax highlighting that allows the programmer to easily see if an identifier or variable is spelled incorrectly [37] and proper indention clearly reveals the code structure [38]. Modern development frameworks also strive for reduced coupling and increased coercion by clearly separating different elements such as the model, view and controller [39]. Another powerful feature of IDEs is the integration of compilers and code analyzers.…”

Section: Statistics Idementioning

confidence: 99%

Statistics-IDE: Supporting the Design of Empirical Experiments for Non-experts During Early Stages of Research Projects

Intelligent Human Systems Integration

2017

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Empirical experimentation and inferential statistics are often perceived as challenging among students and researchers. Yet, empirical experiments are highly relevant and appropriate methods in several areas of ergonomics and human computer interaction. This paper argues that the traditional research proposal written in prose is an ineffective mechanism for ensuring sound experiments. This paper discusses the idea of tool-based support for the design of quantitative experiments. The objective of an experimental design tool is to help the experimenter make correct and wise decisions early in the process by providing feedback on ideas at early stages. We discuss the benefits of the IDE (Integrated Development Environment) paradigm as a platform for designing quantitative experiments.