Computer programming was introduced to primary schools by many countries withthe aim of advancing logic and algorithmic thinking of students. the bulk of a typical syllabus (e.g., in the case of Greece) for computer ...
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ISBN:
(纸本)9783030402716;9783030402709
Computer programming was introduced to primary schools by many countries withthe aim of advancing logic and algorithmic thinking of students. the bulk of a typical syllabus (e.g., in the case of Greece) for computer programming courses at 5th and 6th grade primary school, consists of teaching structured programming concepts. While the comprehension of basic program flow concepts such as branch instructions and loops is of paramount importance, overextending the teaching of the basics may lead to students losing their interest due to lack of challenge. On the other hand, in a mixed classroom environment there exist both students with substantial skills in modern computer technology and others with smaller such experience, e.g., due to societal and economic factors. To avoid discouraging boththe talented pupils by re-visiting the same topics and the less experienced ones by not providing an alternative way of learning, we investigate instructing advanced computer programming concepts in a playful way using pair programming. Results reveal that teaching advanced programming concepts using pair programming can improve the overall programming skills of mixed classroom students.
A methodology is introduced based on first-order logic, for the design and decomposition of abstract domains for abstract interpretation. First, an assertion language is chosen that describes the properties of interes...
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this paper proposes a new knowledge representation language, called QDLP, which extends DLP to deal with uncertain values. A certainty degree interval (a subinterval of [0, 1]) is assigned to each (quantitative) rule....
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ISBN:
(纸本)3540667490
this paper proposes a new knowledge representation language, called QDLP, which extends DLP to deal with uncertain values. A certainty degree interval (a subinterval of [0, 1]) is assigned to each (quantitative) rule. Triangular norms (T-norms) are employed to define calculi for propagating uncertainty information from the premises to the conclusion of a quantitative rule. Negation is considered and the concept of stable model is extended to QDLP. Different T-norms induce different semantics for one given quantitative program. In this sense, QDLP is parameterized and each choice of a T-norm induces a different QDLP language. Each T-norm is eligible for events with determinate relationships (e.g., independence, exclusiveness) between them. Since there are infinitely many T-norms, it turns out that there is a family of infinitely many QDLP languages. this family is carefully studied and the set of QDLP languages which generalize traditional DLP is precisely singled out. Finally the complexity of the main decisional problems arising in the context of QDLP (i.e., Model Checking, Stable Model Checking, Consistency, and Brave Reasoning) is analyzed. It is shown that the complexity of the relevant fragments of QDLP coincides exactly withthe complexity of DLP. that is, reasoning with uncertain values is more general and not harder than reasoning with boolean values.
the design of digital circuits using Cartesian Genetic programming (CGP) has been widely investigated but the evolution of complex combinational logic circuits is a hard task for CGP. We introduce here a new mutation ...
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ISBN:
(纸本)9783030375997;9783030375980
the design of digital circuits using Cartesian Genetic programming (CGP) has been widely investigated but the evolution of complex combinational logic circuits is a hard task for CGP. We introduce here a new mutation operator for CGP that aims to reduce the number of evaluations needed to find a feasible solution by modifying the subgraph of the worst output of the candidate circuits. Also, we propose a variant of the standard evolutionary strategy commonly adopted in CGP, where (i) the Single Active Mutation (SAM) and (ii) the proposed mutation operator is used in order to improve the capacity of CGP in generating feasible circuits. the proposals are applied to a benchmark of combinational logic circuits with multiple outputs and the results obtained are compared to those found by a CGP with SAM. the main advantages observed when both mutation operators are combined are the reduction of the number of objective function evaluations required to find a feasible solution and the improvement in the success rate.
In this paper we show how model checking can be used for the verification of security protocols using a logic of belief. We model principals as processes able to have beliefs. the idea underlying the approach is to tr...
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ISBN:
(纸本)3540672826
In this paper we show how model checking can be used for the verification of security protocols using a logic of belief. We model principals as processes able to have beliefs. the idea underlying the approach is to treat separately the temporal evolution and the belief aspects of principals. therefore, when we consider the temporal evolution, belief formulae are treated as atomic propositions;while the fact that principal A has beliefs about another principal B is modeled as the fact that A has access to a representation of B as a process. As a motivating example, we use the framework proposed to formalize the Andrew protocol.
Inductive logicprogramming (11,P), as any other machine learning or KDD methods, has to deal with imperfect data when applied to real-world problems. Granular Computing (GrC) is a superset of various theories (such a...
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ISBN:
(纸本)0964345692
Inductive logicprogramming (11,P), as any other machine learning or KDD methods, has to deal with imperfect data when applied to real-world problems. Granular Computing (GrC) is a superset of various theories (such as rough sets, fuzzy sets and interval computation) used to handle incompleteness, uncertainty, vagueness, etc. in information systems. this paper investigates the feasibility of applying GrC (especially the rough set theory) to deal with imperfect data in ILP. We list various kinds of imperfect data in ILP (including noise data, too sparse data, missing data, indiscernible data, and too strict bias). For each kind of imperfect data, we try to point out the resulting problem and the potential solution using GrC (or a particular form of GrC such as the rough set theory). the presentation includes formalisms suggested by the authors or other researchers, as well as some general ideas which may give rise to more concrete results in future research.
the proceedings contain 35 papers. the topics discussed include: the evolving relationship between business and information systems;mental distance - and its implications for software and data design for e-business;de...
ISBN:
(纸本)9789898425218
the proceedings contain 35 papers. the topics discussed include: the evolving relationship between business and information systems;mental distance - and its implications for software and data design for e-business;detecting, recognizing and associating facial expressions for emotional behavior;a plea for pluggable programming language features;a systematic literature review of how to introduce data quality requirements into a software product development;towards a catalogue of conflicts among non-functional requirements;using aspect-orientation for software migration;a systematic review on the harmonization of reference models;absolute scales to express stakeholder value for improving support for prioritization;a method and a tool based on a conceptual graph for information systems engineering processes;non-monotonic reasoning for requirements engineering - state diagrams driven by plausible logic;and a change propagation process for distributed software architecture.
the proceedings contain 42 papers. the topics discussed include: curry-style explicit substitutions for the linear and affine lambda calculus;beluga: a framework for programming and reasoning with deductive systems (s...
ISBN:
(纸本)3642142028
the proceedings contain 42 papers. the topics discussed include: curry-style explicit substitutions for the linear and affine lambda calculus;beluga: a framework for programming and reasoning with deductive systems (system description);MCMT: a model checker modulo theories;on hierarchical reasoning in combinations of theories;global caching for coalgebraic description logics;analytic tableaux for higher-order logic with choice;monotonicity inference for higher-order formulas;sledgehammer: judgement day;multi-prover verification of floating-point programs;MUNCH - automated reasoner for sets and multisets;a slice-based decision procedure for type-based partial orders;hierarchical reasoning for the verification of parametric systems;interpolation and symbol elimination in vampire;automated reasoning for relational probabilistic knowledge representation;and herod and pilate: two tableau provers for basic hybrid logic.
the proceedings contain 29 papers. the topics discussed include: exploiting algebraic laws to improve mechanized axiomatizations;positive fragments of coalgebraic logics;many-valued relation lifting and moss' coal...
ISBN:
(纸本)9783642402050
the proceedings contain 29 papers. the topics discussed include: exploiting algebraic laws to improve mechanized axiomatizations;positive fragments of coalgebraic logics;many-valued relation lifting and moss' coalgebraic logic;saturated semantics for coalgebraic logicprogramming;presenting distributive laws;interaction and observation: categorical semantics of reactive systems trough dialgebras;homomorphisms of coalgebras from predicate liftings;trace semantics via generic observations;full abstraction for fair testing in CCS;a simple case of rationality of escalation;coalgebras with symmetries and modeling quantum systems;from operational chu duality to coalgebraic quantum symmetry;noninterfering schedulers: when possibilistic noninterference implies probabilistic noninterference;and simulations and bisimulations for coalgebraic modal logics.
In this article the contribution of experiential learning, gamification and emerging technologies to Python programming language teaching is attempted to be sketched. Four scenarios were designed in order to constitut...
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ISBN:
(纸本)9781728143606
In this article the contribution of experiential learning, gamification and emerging technologies to Python programming language teaching is attempted to be sketched. Four scenarios were designed in order to constitute a new teaching proposal for the consolidation of specific modules, incorporating elements of dynamic games, emerging technology and approaching the subject that they are dealing with, in an experiential way in an authentic learning framework by solving problems of everyday life. the main approach of the scenarios is that of social constructivism. A study was conducted to assess the impact of the design of scenarios on learner motivation. the sample of the survey was 15 undergraduate students of the Department of Informatics with Applications in Biomedicine of the University of thessaly. After completing each scenario, they completed a questionnaire based on the CIS questionnaire survey, which was designed by Keller in 1987 with Likert's 5-step scale questions on the variables motivation, attention-relevance, confidence-satisfaction that are the components of the Kellers ARCS motivation model. the results showed that designing learning scenarios by combining experiential learning, gamification and the use of emerging technologies strengthens the motivation of trainees and leads to the achievement of learning goals.
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