This is a guidebook for those who want to use computational experiments to support their work in algorithm design and analysis. Numerous case studies and examples show how to apply these concepts. All the necessary concepts in computer architecture and data analysis are covered so that the book can be used by anyone who has taken a course or two in data structures and algorithms.

Takes the human-computer interaction researcher through the complete experimental process, from identifying a research question, to conducting an experiment and analysing the results.

This book constitutes the refereed proceedings of the 13th International Symposium on Experimental Algorithms, SEA 2014, held in Copenhagen, Denmark, in June/July 2014. The 36 revised full papers presented together with 3 invited presentations were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on combinatorial optimization, data structures, graph drawing, shortest path, strings, graph algorithms and suffix structures.

This book constitutes the refereed proceedings of the 7th International Workshop on Experimental and Efficient Algorithms, WEA 2008, held in Provincetown, MA, USA, in May/June 2008. The 26 revised full papers were carefully reviewed and selected from numerous submissions and present current research on experimental evaluation and engineering of algorithms, as well as in various aspects of computational optimization and its applications. Special focus is put on the use of experimental methods to guide the design, analysis, implementation, and evaluation of algorithms, heuristics, and optimization programs.

Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications. Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.

Fostering Pedagogy Through Micro and Adaptive Learning in Higher Education: Trends, Tools, and Applications is a timely and groundbreaking book that addresses the challenges of engaging the digital generations in the teaching-learning process, intensified by the pandemic. Written by Ricardo Queirós, a renowned researcher in e-learning interoperability and programming languages, the book offers a unique perspective on using micro and adaptive learning approaches to create immersive and personalized environments that cater to the learning styles and paces of diverse students. The book covers innovative trends, tools, and applications that enable educators to implement pedagogical practices that enhance the teaching-learning experience. It explores topics such as artificial intelligence in education, adaptive hypermedia, differentiated instruction, and micro-gamification design, providing readers with practical tools to create personalized and immersive learning environments. This book is a valuable resource for professors of any domain, practitioners, and students pursuing education, as well as research scholars looking to expand their understanding of e-learning and pedagogical innovation. It is a must-read for anyone interested in the future of education and how digital technologies can be leveraged to create engaging and immersive learning environments.