Institut für Informatik und Computational Science
Refine
Year of publication
- 2015 (49) (remove)
Document Type
- Article (49) (remove)
Language
- English (49) (remove)
Keywords
- Computer Science Education (4)
- Competence Measurement (3)
- Secondary Education (3)
- Answer set programming (2)
- Big Data (2)
- Competence Modelling (2)
- Computational thinking (2)
- Informatics Education (2)
- Informatics Modelling (2)
- Informatics System Application (2)
- Informatics System Comprehension (2)
- computational thinking (2)
- 21st century skills, (1)
- ABRACADABRA (1)
- AODV (1)
- Achievement (1)
- Activity Theory (1)
- Activity-orientated Learning (1)
- Ad hoc routing (1)
- Arduino (1)
- Assessment (1)
- Austria (1)
- Backdoors (1)
- Bloom’s Taxonomy (1)
- Boolean logic models (1)
- CS concepts (1)
- Capability approach (1)
- Challenges (1)
- Cluster Computing (1)
- Cognitive Skills (1)
- Combinatorial multi-objective optimization (1)
- Competences (1)
- Competencies (1)
- Computational Thinking (1)
- Computational complexity (1)
- Computational grid (1)
- Computer Science (1)
- Computer Science in Context (1)
- Computing (1)
- Contest (1)
- Contextualisation (1)
- Contradictions (1)
- Curriculum (1)
- Curriculum Development (1)
- Data Analysis (1)
- Data Management (1)
- Data Privacy (1)
- Databases (1)
- Defining characteristics of physical computing (1)
- Digital Competence (1)
- Digital Education (1)
- Digital Revolution (1)
- Dynamic assessment (1)
- E-learning (1)
- Early Literacy (1)
- Educational Standards (1)
- Educational game (1)
- Educational software (1)
- Embedded Systems (1)
- Euclid’s algorithm (1)
- Facebook (1)
- Fibonacci numbers (1)
- Function (1)
- Fundamental Ideas (1)
- ICT Competence (1)
- ICT competencies (1)
- ICT skills (1)
- Informatics (1)
- Inquiry-based Learning (1)
- Interface design (1)
- Kernelization (1)
- Key Competencies (1)
- Learners (1)
- Learning Fields (1)
- Learning ecology (1)
- Learning interfaces development (1)
- Learning with ICT (1)
- Load Balancing (1)
- Location awareness (1)
- Logarithm (1)
- Lower Secondary Level (1)
- MOOCs (1)
- Massive Open Online Courses (1)
- Measurement (1)
- Mobile application (1)
- Multiple interpretation scheme (1)
- Music Technology (1)
- NUI (1)
- Natural Science Education (1)
- NoSQL (1)
- Norway (1)
- Novice programmers (1)
- Parallel job execution time estimation (1)
- Parameterized complexity (1)
- Pedagogical content knowledge (1)
- Performance Evaluation (1)
- Pervasive computing (1)
- Physical Science (1)
- Problem Solving (1)
- RSA triangle (1)
- Recommendations for CS-Curricula in Higher Education (1)
- Sensors (1)
- Signaling transduction networks (1)
- Small Private Online Courses (1)
- Social (1)
- Systems biology (1)
- Tasks (1)
- Teacher perceptions (1)
- Teachers (1)
- Teaching information security (1)
- Technology proficiency (1)
- Terminology (1)
- Tests (1)
- Theory (1)
- User submission pattern (1)
- Vocational Education (1)
- Young People (1)
- abstraction (1)
- algorithm schedules (1)
- analogical thinking (1)
- answer set programming (1)
- binary representation (1)
- binary search (1)
- classroom language (1)
- cognitive modifiability (1)
- collaborative learning (1)
- competence (1)
- competencies (1)
- competency (1)
- complexity (1)
- comprehension (1)
- computer science education (1)
- computer science teachers (1)
- conductive argument (1)
- cs4fn (1)
- curriculum theory (1)
- digitally-enabled pedagogies (1)
- divide and conquer (1)
- e-mentoring (1)
- eLectures (1)
- education (1)
- education and public policy (1)
- educational programming (1)
- educational systems (1)
- edutainment (1)
- environments (1)
- exponentiation (1)
- external ambiguity (1)
- formal argumentation systems (1)
- fun (1)
- high school (1)
- higher (1)
- informal and formal learning (1)
- informal logic (1)
- informatics education (1)
- innovation (1)
- interactive course (1)
- interactive workshop (1)
- internal ambiguity (1)
- key competences in physical computing (1)
- key competencies (1)
- kinaesthetic teaching (1)
- learning (1)
- mediated learning experience (1)
- mobile learning (1)
- mobile technologies and apps (1)
- networks (1)
- o-ambiguity (1)
- operating system (1)
- organisational evolution (1)
- paper prototyping (1)
- parameter (1)
- pedagogy (1)
- personal (1)
- personal response systems (1)
- philosophical foundation of informatics pedagogy (1)
- physical computing tools (1)
- portfolio-based solving (1)
- pre-primary level (1)
- premise acceptability (1)
- primary education (1)
- primary level (1)
- problem-solving (1)
- professional development (1)
- programming (1)
- programming in context (1)
- real arguments (1)
- regular language (1)
- relevance (1)
- secondary computer science education (1)
- secondary education (1)
- self-efficacy (1)
- social media (1)
- student activation (1)
- student experience (1)
- student perceptions (1)
- students’ conceptions (1)
- students’ knowledge (1)
- sufficiency (1)
- teacher competencies (1)
- teaching informatics in general education (1)
- tele-teaching (1)
- tools (1)
- tracing (1)
- user-centred (1)
- video annotation (1)
- virtual reality (1)
- ‘unplugged’ computing (1)
Institute
Scheduling performance in computational grid can potentially benefit a lot from accurate execution time estimation for parallel jobs. Most existing approaches for the parallel job execution time estimation, however, require ample past job traces and the explicit correlations between the job execution time and the outer layout parameters such as the consumed processor numbers, the user-estimated execution time and the job ID, which are hard to obtain or reveal. This paper presents and evaluates a novel execution time estimation approach for parallel jobs, the user-behavior clustering for execution time estimation, which can give more accurate execution time estimation for parallel jobs through exploring the job similarity and revealing the user submission patterns. Experiment results show that compared to the state-of-art algorithms, our approach can improve the accuracy of the job execution time estimation up to 5.6 %, meanwhile the time that our approach spends on calculation can be reduced up to 3.8 %.
A multiple interpretation scheme is an ordered sequence of morphisms. The ordered multiple interpretation of a word is obtained by concatenating the images of that word in the given order of morphisms. The arbitrary multiple interpretation of a word is the semigroup generated by the images of that word. These interpretations are naturally extended to languages. Four types of ambiguity of multiple interpretation schemata on a language are defined: o-ambiguity, internal ambiguity, weakly external ambiguity and strongly external ambiguity. We investigate the problem of deciding whether a multiple interpretation scheme is ambiguous on regular languages.
Algorithm selection (AS) techniques - which involve choosing from a set of algorithms the one expected to solve a given problem instance most efficiently - have substantially improved the state of the art in solving many prominent AI problems, such as SAT, CSP, ASP, MAXSAT and QBF. Although several AS procedures have been introduced, not too surprisingly, none of them dominates all others across all AS scenarios. Furthermore, these procedures have parameters whose optimal values vary across AS scenarios. This holds specifically for the machine learning techniques that form the core of current AS procedures, and for their hyperparameters. Therefore, to successfully apply AS to new problems, algorithms and benchmark sets, two questions need to be answered: (i) how to select an AS approach and (ii) how to set its parameters effectively. We address both of these problems simultaneously by using automated algorithm configuration. Specifically, we demonstrate that we can automatically configure claspfolio 2, which implements a large variety of different AS approaches and their respective parameters in a single, highly-parameterized algorithm framework. Our approach, dubbed AutoFolio, allows researchers and practitioners across a broad range of applications to exploit the combined power of many different AS methods. We demonstrate AutoFolio can significantly improve the performance of claspfolio 2 on 8 out of the 13 scenarios from the Algorithm Selection Library, leads to new state-of-the-art algorithm selectors for 7 of these scenarios, and matches state-of-the-art performance (statistically) on all other scenarios. Compared to the best single algorithm for each AS scenario, AutoFolio achieves average speedup factors between 1.3 and 15.4.
Although Boolean Constraint Technology has made tremendous progress over the last decade, the efficacy of state-of-the-art solvers is known to vary considerably across different types of problem instances, and is known to depend strongly on algorithm parameters. This problem was addressed by means of a simple, yet effective approach using handmade, uniform, and unordered schedules of multiple solvers in ppfolio, which showed very impressive performance in the 2011 Satisfiability Testing (SAT) Competition. Inspired by this, we take advantage of the modeling and solving capacities of Answer Set Programming (ASP) to automatically determine more refined, that is, nonuniform and ordered solver schedules from the existing benchmarking data. We begin by formulating the determination of such schedules as multi-criteria optimization problems and provide corresponding ASP encodings. The resulting encodings are easily customizable for different settings, and the computation of optimum schedules can mostly be done in the blink of an eye, even when dealing with large runtime data sets stemming from many solvers on hundreds to thousands of instances. Also, the fact that our approach can be customized easily enabled us to swiftly adapt it to generate parallel schedules for multi-processor machines.
In this paper we describe the recent state of our research
project concerning computer science teachers’ knowledge on students’
cognition. We did a comprehensive analysis of textbooks, curricula
and other resources, which give teachers guidance to formulate assignments.
In comparison to other subjects there are only a few concepts
and strategies taught to prospective computer science teachers in university.
We summarize them and given an overview on our empirical
approach to measure this knowledge.
Answer Set Programming (ASP) is an increasingly popular framework for declarative programming that admits the description of problems by means of rules and constraints that form a disjunctive logic program. In particular, many Al problems such as reasoning in a nonmonotonic setting can be directly formulated in ASP. Although the main problems of ASP are of high computational complexity, complete for the second level of the Polynomial Hierarchy, several restrictions of ASP have been identified in the literature, under which ASP problems become tractable.
In this paper we use the concept of backdoors to identify new restrictions that make ASP problems tractable. Small backdoors are sets of atoms that represent "clever reasoning shortcuts" through the search space and represent a hidden structure in the problem input. The concept of backdoors is widely used in theoretical investigations in the areas of propositional satisfiability and constraint satisfaction. We show that it can be fruitfully adapted to ASP. We demonstrate how backdoors can serve as a unifying framework that accommodates several tractable restrictions of ASP known from the literature. Furthermore, we show how backdoors allow us to deploy recent algorithmic results from parameterized complexity theory to the domain of answer set programming. (C) 2015 Elsevier B.V. All rights reserved.
BugHunt
(2015)
Competencies related to operating systems and computer
security are usually taught systematically. In this paper we present
a different approach, in which students have to remove virus-like
behaviour on their respective computers, which has been induced by
software developed for this purpose. They have to develop appropriate
problem-solving strategies and thereby explore essential elements of
the operating system. The approach was implemented exemplarily in
two computer science courses at a regional general upper secondary
school and showed great motivation and interest in the participating
students.
The paper presents two approaches to the development of
a Computer Science Competence Model for the needs of curriculum
development and evaluation in Higher Education. A normativetheoretical
approach is based on the AKT and ACM/IEEE curriculum
and will be used within the recommendations of the German
Informatics Society (GI) for the design of CS curricula. An empirically
oriented approach refines the categories of the first one with regard to
specific subject areas by conducting content analysis on CS curricula of
important universities from several countries. The refined model will be
used for the needs of students’ e-assessment and subsequent affirmative
action of the CS departments.
Computational Thinking
(2015)
Digital technology has radically changed the way people
work in industry, finance, services, media and commerce. Informatics
has contributed to the scientific and technological development of our
society in general and to the digital revolution in particular. Computational
thinking is the term indicating the key ideas of this discipline that
might be included in the key competencies underlying the curriculum
of compulsory education. The educational potential of informatics has
a history dating back to the sixties. In this article, we briefly revisit this
history looking for lessons learned. In particular, we focus on experiences
of teaching and learning programming. However, computational
thinking is more than coding. It is a way of thinking and practicing interactive
dynamic modeling with computers. We advocate that learners
can practice computational thinking in playful contexts where they can
develop personal projects, for example building videogames and/or robots,
share and discuss their construction with others. In our view, this
approach allows an integration of computational thinking in the K-12
curriculum across disciplines.
This paper originated from discussions about the need for
important changes in the curriculum for Computing including two focus
group meetings at IFIP conferences over the last two years. The
paper examines how recent developments in curriculum, together with
insights from curriculum thinking in other subject areas, especially mathematics
and science, can inform curriculum design for Computing.
The analysis presented in the paper provides insights into the complexity
of curriculum design as well as identifying important constraints and
considerations for the ongoing development of a vision and framework
for a Computing curriculum.