004 Datenverarbeitung; Informatik
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In recent years, many efforts have been made to apply image processing techniques for plant leaf identification. However, categorizing leaf images at the cultivar/variety level, because of the very low inter-class variability, is still a challenging task. In this research, we propose an automatic discriminative method based on convolutional neural networks (CNNs) for classifying 12 different cultivars of common beans that belong to three various species. We show that employing advanced loss functions, such as Additive Angular Margin Loss and Large Margin Cosine Loss, instead of the standard softmax loss function for the classification can yield better discrimination between classes and thereby mitigate the problem of low inter-class variability. The method was evaluated by classifying species (level I), cultivars from the same species (level II), and cultivars from different species (level III), based on images from the leaf foreside and backside. The results indicate that the performance of the classification algorithm on the leaf backside image dataset is superior. The maximum mean classification accuracies of 95.86, 91.37 and 86.87% were obtained at the levels I, II and III, respectively. The proposed method outperforms the previous relevant works and provides a reliable approach for plant cultivars identification.
The intensity of cosmic radiation may differ over five orders of magnitude within a few hours or days during the Solar Particle Events (SPEs), thus increasing for several orders of magnitude the probability of Single Event Upsets (SEUs) in space-borne electronic systems. Therefore, it is vital to enable the early detection of the SEU rate changes in order to ensure timely activation of dynamic radiation hardening measures. In this paper, an embedded approach for the prediction of SPEs and SRAM SEU rate is presented. The proposed solution combines the real-time SRAM-based SEU monitor, the offline-trained machine learning model and online learning algorithm for the prediction. With respect to the state-of-the-art, our solution brings the following benefits: (1) Use of existing on-chip data storage SRAM as a particle detector, thus minimizing the hardware and power overhead, (2) Prediction of SRAM SEU rate one hour in advance, with the fine-grained hourly tracking of SEU variations during SPEs as well as under normal conditions, (3) Online optimization of the prediction model for enhancing the prediction accuracy during run-time, (4) Negligible cost of hardware accelerator design for the implementation of selected machine learning model and online learning algorithm. The proposed design is intended for a highly dependable and self-adaptive multiprocessing system employed in space applications, allowing to trigger the radiation mitigation mechanisms before the onset of high radiation levels.
In control theory, to solve a finite-horizon sequential decision problem (SDP) commonly means to find a list of decision rules that result in an optimal expected total reward (or cost) when taking a given number of decision steps. SDPs are routinely solved using Bellman's backward induction. Textbook authors (e.g. Bertsekas or Puterman) typically give more or less formal proofs to show that the backward induction algorithm is correct as solution method for deterministic and stochastic SDPs. Botta, Jansson and Ionescu propose a generic framework for finite horizon, monadic SDPs together with a monadic version of backward induction for solving such SDPs. In monadic SDPs, the monad captures a generic notion of uncertainty, while a generic measure function aggregates rewards. In the present paper, we define a notion of correctness for monadic SDPs and identify three conditions that allow us to prove a correctness result for monadic backward induction that is comparable to textbook correctness proofs for ordinary backward induction. The conditions that we impose are fairly general and can be cast in category-theoretical terms using the notion of Eilenberg-Moore algebra. They hold in familiar settings like those of deterministic or stochastic SDPs, but we also give examples in which they fail. Our results show that backward induction can safely be employed for a broader class of SDPs than usually treated in textbooks. However, they also rule out certain instances that were considered admissible in the context of Botta et al. 's generic framework. Our development is formalised in Idris as an extension of the Botta et al. framework and the sources are available as supplementary material.
Machine learning for improvement of thermal conditions inside a hybrid ventilated animal building
(2021)
In buildings with hybrid ventilation, natural ventilation opening positions (windows), mechanical ventilation rates, heating, and cooling are manipulated to maintain desired thermal conditions. The indoor temperature is regulated solely by ventilation (natural and mechanical) when the external conditions are favorable to save external heating and cooling energy. The ventilation parameters are determined by a rule-based control scheme, which is not optimal. This study proposes a methodology to enable real-time optimum control of ventilation parameters. We developed offline prediction models to estimate future thermal conditions from the data collected from building in operation. The developed offline model is then used to find the optimal controllable ventilation parameters in real-time to minimize the setpoint deviation in the building. With the proposed methodology, the experimental building's setpoint deviation improved for 87% of time, on average, by 0.53 degrees C compared to the current deviations.
Student teachers often struggle to keep track of everything that is happening in the classroom, and particularly to notice and respond when students cause disruptions. The complexity of the classroom environment is a potential contributing factor that has not been empirically tested. In this experimental study, we utilized a virtual reality (VR) classroom to examine whether classroom complexity affects the likelihood of student teachers noticing disruptions and how they react after noticing. Classroom complexity was operationalized as the number of disruptions and the existence of overlapping disruptions (multidimensionality) as well as the existence of parallel teaching tasks (simultaneity). Results showed that student teachers (n = 50) were less likely to notice the scripted disruptions, and also less likely to respond to the disruptions in a comprehensive and effortful manner when facing greater complexity. These results may have implications for both teacher training and the design of VR for training or research purpose. This study contributes to the field from two aspects: 1) it revealed how features of the classroom environment can affect student teachers' noticing of and reaction to disruptions; and 2) it extends the functionality of the VR environment-from a teacher training tool to a testbed of fundamental classroom processes that are difficult to manipulate in real-life.
The use of neural networks is considered as the state of the art in the field of image classification. A large number of different networks are available for this purpose, which, appropriately trained, permit a high level of classification accuracy. Typically, these networks are applied to uncompressed image data, since a corresponding training was also carried out using image data of similar high quality. However, if image data contains image errors, the classification accuracy deteriorates drastically. This applies in particular to coding artifacts which occur due to image and video compression. Typical application scenarios for video compression are narrowband transmission channels for which video coding is required but a subsequent classification is to be carried out on the receiver side. In this paper we present a special H.264/Advanced Video Codec (AVC) based video codec that allows certain regions of a picture to be coded with near constant picture quality in order to allow a reliable classification using neural networks, whereas the remaining image will be coded using constant bit rate. We have combined this feature with the ability to run with lowest latency properties, which is usually also required in remote control applications scenarios. The codec has been implemented as a fully hardwired High Definition video capable hardware architecture which is suitable for Field Programmable Gate Arrays.
Image feature detection is a key task in computer vision. Scale Invariant Feature Transform (SIFT) is a prevalent and well known algorithm for robust feature detection. However, it is computationally demanding and software implementations are not applicable for real-time performance. In this paper, a versatile and pipelined hardware implementation is proposed, that is capable of computing keypoints and rotation invariant descriptors on-chip. All computations are performed in single precision floating-point format which makes it possible to implement the original algorithm with little alteration. Various rotation resolutions and filter kernel sizes are supported for images of any resolution up to ultra-high definition. For full high definition images, 84 fps can be processed. Ultra high definition images can be processed at 21 fps.
We introduce a new measure of descriptional complexity on finite automata, called the number of active states. Roughly speaking, the number of active states of an automaton A on input w counts the number of different states visited during the most economic computation of the automaton A for the word w. This concept generalizes to finite automata and regular languages in a straightforward way. We show that the number of active states of both finite automata and regular languages is computable, even with respect to nondeterministic finite automata. We further compare the number of active states to related measures for regular languages. In particular, we show incomparability to the radius of regular languages and that the difference between the number of active states and the total number of states needed in finite automata for a regular language can be of exponential order.
User Experience (UX) describes the holistic experience of a user before, during, and after interaction with a platform, product, or service. UX adds value and attraction to their sole functionality and is therefore highly relevant for firms. The increased interest in UX has produced a vast amount of scholarly research since 1983. The research field is, therefore, complex and scattered. Conducting a bibliometric analysis, we aim at structuring the field quantitatively and rather abstractly. We employed citation analyses, co-citation analyses, and content analyses to evaluate productivity and impact of extant research. We suggest that future research should focus more on business and management related topics.
We study the concept of reversibility in connection with parallel communicating systems of finite automata (PCFA in short). We define the notion of reversibility in the case of PCFA (also covering the non-deterministic case) and discuss the relationship of the reversibility of the systems and the reversibility of its components. We show that a system can be reversible with non-reversible components, and the other way around, the reversibility of the components does not necessarily imply the reversibility of the system as a whole. We also investigate the computational power of deterministic centralized reversible PCFA. We show that these very simple types of PCFA (returning or non-returning) can recognize regular languages which cannot be accepted by reversible (deterministic) finite automata, and that they can even accept languages that are not context-free. We also separate the deterministic and non-deterministic variants in the case of systems with non-returning communication. We show that there are languages accepted by non-deterministic centralized PCFA, which cannot be recognized by any deterministic variant of the same type.
M-rate 0L systems are interactionless Lindenmayer systems together with a function assigning to every string a set of multisets of productions that may be applied simultaneously to the string. Some questions that have been left open in the forerunner papers are examined, and the computational power of deterministic M-rate 0L systems is investigated, where also tabled and extended variants are taken into consideration.
Research publications and data nowadays should be publicly available on the internet and, theoretically, usable for everyone to develop further research, products, or services. The long-term accessibility of research data is, therefore, fundamental in the economy of the research production process. However, the availability of data is not sufficient by itself, but also their quality must be verifiable. Measures to ensure reuse and reproducibility need to include the entire research life cycle, from the experimental design to the generation of data, quality control, statistical analysis, interpretation, and validation of the results. Hence, high-quality records, particularly for providing a string of documents for the verifiable origin of data, are essential elements that can act as a certificate for potential users (customers). These records also improve the traceability and transparency of data and processes, therefore, improving the reliability of results. Standards for data acquisition, analysis, and documentation have been fostered in the last decade driven by grassroot initiatives of researchers and organizations such as the Research Data Alliance (RDA). Nevertheless, what is still largely missing in the life science academic research are agreed procedures for complex routine research workflows. Here, well-crafted documentation like standard operating procedures (SOPs) offer clear direction and instructions specifically designed to avoid deviations as an absolute necessity for reproducibility. Therefore, this paper provides a standardized workflow that explains step by step how to write an SOP to be used as a starting point for appropriate research documentation.
The aim of our project design space exploration with answer set programming is to develop a general framework based on Answer Set Programming (ASP) that finds valid solutions to the system design problem and simultaneously performs Design Space Exploration (DSE) to find the most favorable alternatives. We leverage recent developments in ASP solving that allow for tight integration of background theories to create a holistic framework for effective DSE.
The Potsdam answer set solving collection, or Potassco for short, bundles various tools implementing and/or applying answer set programming. The article at hand succeeds an earlier description of the Potassco project published in Gebser et al. (AI Commun 24(2):107-124, 2011). Hence, we concentrate in what follows on the major features of the most recent, fifth generation of the ASP system clingo and highlight some recent resulting application systems.
Answer Set Programming faces an increasing popularity for problem solving in various domains. While its modeling language allows us to express many complex problems in an easy way, its solving technology enables their effective resolution. In what follows, we detail some of the key factors of its success. Answer Set Programming [ASP; Brewka et al. Commun ACM 54(12):92–103, (2011)] is seeing a rapid proliferation in academia and industry due to its easy and flexible way to model and solve knowledge-intense combinatorial (optimization) problems. To this end, ASP offers a high-level modeling language paired with high-performance solving technology. As a result, ASP systems provide out-off-the-box, general-purpose search engines that allow for enumerating (optimal) solutions. They are represented as answer sets, each being a set of atoms representing a solution. The declarative approach of ASP allows a user to concentrate on a problem’s specification rather than the computational means to solve it. This makes ASP a prime candidate for rapid prototyping and an attractive tool for teaching key AI techniques since complex problems can be expressed in a succinct and elaboration tolerant way. This is eased by the tuning of ASP’s modeling language to knowledge representation and reasoning (KRR). The resulting impact is nicely reflected by a growing range of successful applications of ASP [Erdem et al. AI Mag 37(3):53–68, 2016; Falkner et al. Industrial applications of answer set programming. K++nstliche Intelligenz (2018)]
We introduce a type and effect system, for an imperative object calculus, which infers sharing possibly introduced by the evaluation of an expression, represented as an equivalence relation among its free variables. This direct representation of sharing effects at the syntactic level allows us to express in a natural way, and to generalize, widely-used notions in literature, notably uniqueness and borrowing. Moreover, the calculus is pure in the sense that reduction is defined on language terms only, since they directly encode store. The advantage of this non-standard execution model with respect to a behaviorally equivalent standard model using a global auxiliary structure is that reachability relations among references are partly encoded by scoping. (C) 2018 Elsevier B.V. All rights reserved.
plasp 3
(2019)
We describe the new version of the Planning Domain Definition Language (PDDL)-to-Answer Set Programming (ASP) translator plasp. First, it widens the range of accepted PDDL features. Second, it contains novel planning encodings, some inspired by Satisfiability Testing (SAT) planning and others exploiting ASP features such as well-foundedness. All of them are designed for handling multivalued fluents in order to capture both PDDL as well as SAS planning formats. Third, enabled by multishot ASP solving, it offers advanced planning algorithms also borrowed from SAT planning. As a result, plasp provides us with an ASP-based framework for studying a variety of planning techniques in a uniform setting. Finally, we demonstrate in an empirical analysis that these techniques have a significant impact on the performance of ASP planning.
Multi-sided platforms (MSP) strongly affect markets and play a crucial part within the digital and networked economy. Although empirical evidence indicates their occurrence in many industries, research has not investigated the game-changing impact of MSP on traditional markets to a sufficient extent. More specifically, we have little knowledge of how MSP affect value creation and customer interaction in entire markets, exploiting the potential of digital technologies to offer new value propositions. Our paper addresses this research gap and provides an initial systematic approach to analyze the impact of MSP on the insurance industry. For this purpose, we analyze the state of the art in research and practice in order to develop a reference model of the value network for the insurance industry. On this basis, we conduct a case-study analysis to discover and analyze roles which are occupied or even newly created by MSP. As a final step, we categorize MSP with regard to their relation to traditional insurance companies, resulting in a classification scheme with four MSP standard types: Competition, Coordination, Cooperation, Collaboration.
Solving problems combining task and motion planning requires searching across a symbolic search space and a geometric search space. Because of the semantic gap between symbolic and geometric representations, symbolic sequences of actions are not guaranteed to be geometrically feasible. This compels us to search in the combined search space, in which frequent backtracks between symbolic and geometric levels make the search inefficient.We address this problem by guiding symbolic search with rich information extracted from the geometric level through culprit detection mechanisms.
In this project I constructed a workflow that takes a DNA sequence as input and provides a phylogenetic tree, consisting of the input sequence and other sequences which were found during a database search. In this phylogenetic tree the sequences are arranged depending on similarities. In bioinformatics, constructing phylogenetic trees is often used to explore the evolutionary relationships of genes or organisms and to understand the mechanisms of evolution itself.
Spotlocator is a game wherein people have to guess the spots of where photos were taken. The photos of a defined area for each game are from panoramio.com. They are published at http://spotlocator. drupalgardens.com with an ID. Everyone can guess the photo spots by sending a special tweet via Twitter that contains the hashtag #spotlocator, the guessed coordinates and the ID of the photo. An evaluation is published for all tweets. The players are informed about the distance to the real photo spots and the positions are shown on a map.
Exploratory Data Analysis
(2014)
In bioinformatics the term exploratory data analysis refers to different methods to get an overview of large biological data sets. Hence, it helps to create a framework for further analysis and hypothesis testing. The workflow facilitates this first important step of the data analysis created by high-throughput technologies. The results are different plots showing the structure of the measurements. The goal of the workflow is the automatization of the exploratory data analysis, but also the flexibility should be guaranteed. The basic tool is the free software R.
The protein classification workflow described in this report enables users to get information about a novel protein sequence automatically. The information is derived by different bioinformatic analysis tools which calculate or predict features of a protein sequence. Also, databases are used to compare the novel sequence with known proteins.
Lessons Learned
(2014)
This chapter summarizes the experience and the lessons we learned concerning the application of the jABC as a framework for design and execution of scientific workflows. It reports experiences from the domain modeling (especially service integration) and workflow design phases and evaluates the resulting models statistically with respect to the SIB library and hierarchy levels.
The Course's SIB Libraries
(2014)
This chapter gives a detailed description of the service framework underlying all the example projects that form the foundation of this book. It describes the different SIB libraries that we made available for the course “Process modeling in the natural sciences” to provide the functionality that was required for the envisaged applications. The students used these SIB libraries to realize their projects.
A major part of the scientific experiments that are carried out today requires thorough computational support. While database and algorithm providers face the problem of bundling resources to create and sustain powerful computation nodes, the users have to deal with combining sets of (remote) services into specific data analysis and transformation processes. Today’s attention to “big data” amplifies the issues of size, heterogeneity, and process-level diversity/integration. In the last decade, especially workflow-based approaches to deal with these processes have enjoyed great popularity. This book concerns a particularly agile and model-driven approach to manage scientific workflows that is based on the XMDD paradigm. In this chapter we explain the scope and purpose of the book, briefly describe the concepts and technologies of the XMDD paradigm, explain the principal differences to related approaches, and outline the structure of the book.
We summarize here the main characteristics and features of the jABC framework, used in the case studies as a graphical tool for modeling scientific processes and workflows. As a comprehensive environment for service-oriented modeling and design according to the XMDD (eXtreme Model-Driven Design) paradigm, the jABC offers much more than the pure modeling capability. Associated technologies and plugins provide in fact means for a rich variety of supporting functionality, such as remote service integration, taxonomical service classification, model execution, model verification, model synthesis, and model compilation. We describe here in short both the essential jABC features and the service integration philosophy followed in the environment. In our work over the last years we have seen that this kind of service definition and provisioning platform has the potential to become a core technology in interdisciplinary service orchestration and technology transfer: Domain experts, like scientists not specially trained in computer science, directly define complex service orchestrations as process models and use efficient and complex domain-specific tools in a simple and intuitive way.
A lot has been published about the competencies needed by
students in the 21st century (Ravenscroft et al., 2012). However, equally
important are the competencies needed by educators in the new era
of digital education. We review the key competencies for educators in
light of the new methods of teaching and learning proposed by Massive
Open Online Courses (MOOCs) and their on-campus counterparts,
Small Private Online Courses (SPOCs).
Participants of this workshop will be confronted exemplarily
with a considerable inconsistency of global Informatics education at
lower secondary level. More importantly, they are invited to contribute
actively on this issue in form of short case studies of their countries.
Until now, very few countries have been successful in implementing
Informatics or Computing at primary and lower secondary level. The
spectrum from digital literacy to informatics, particularly as a discipline
in its own right, has not really achieved a breakthrough and seems to
be underrepresented for these age groups. The goal of this workshop
is not only to discuss the anamnesis and diagnosis of this fragmented
field, but also to discuss and suggest viable forms of therapy in form of
setting educational standards. Making visible good practices in some
countries and comparing successful approaches are rewarding tasks for
this workshop.
Discussing and defining common educational standards on a transcontinental
level for the age group of 14 to 15 years old students in a readable,
assessable and acceptable form should keep the participants of this
workshop active beyond the limited time at the workshop.
Let’s talk about CS!
(2015)
To communicate about a science is the most important key
competence in education for any science. Without communication we
cannot teach, so teachers should reflect about the language they use in
class properly. But the language students and teachers use to communicate
about their CS courses is very heterogeneous, inconsistent and
deeply influenced by tool names. There is a big lack of research and
discussion in CS education regarding the terminology and the role of
concepts and tools in our science. We don’t have a consistent set of
terminology that we agree on to be helpful for learning our science.
This makes it nearly impossible to do research on CS competencies as
long as we have not agreed on the names we use to describe these. This
workshop intends to provide room to fill with discussion and first ideas
for future research in this field.
ProtoSense
(2015)
The poster and abstract describe the importance of teaching
information security in school. After a short description of information
security and important aspects, I will show, how information security
fits into different guidelines or models for computer science educations
and that it is therefore on of the key competencies. Afterwards I will
present you a rough insight of teaching information security in Austria.
Current curricular trends require teachers in Baden-
Wuerttemberg (Germany) to integrate Computer Science (CS) into
traditional subjects, such as Physical Science. However, concrete guidelines
are missing. To fill this gap, we outline an approach where a
microcontroller is used to perform and evaluate measurements in the
Physical Science classroom.
Using the open-source Arduino platform, we expect students to acquire
and develop both CS and Physical Science competencies by using a
self-programmed microcontroller. In addition to this combined development
of competencies in Physical Science and CS, the subject matter
will be embedded in suitable contexts and learning environments,
such as weather and climate.
Think logarithmically!
(2015)
We discuss here a number of algorithmic topics which we
use in our teaching and in learning of mathematics and informatics to
illustrate and document the power of logarithm in designing very efficient
algorithms and computations – logarithmic thinking is one of the
most important key competencies for solving real world practical problems.
We demonstrate also how to introduce logarithm independently
of mathematical formalism using a conceptual model for reducing a
problem size by at least half. It is quite surprising that the idea, which
leads to logarithm, is present in Euclid’s algorithm described almost
2000 years before John Napier invented logarithm.
A project involving the composition of a number of pieces
of music by public participants revealed levels of engagement with and
mastery of complex music technologies by a number of secondary student
volunteers. This paper reports briefly on some initial findings of
that project and seeks to illuminate an understanding of computational
thinking across the curriculum.
Physical computing covers the design and realization of interactive
objects and installations and allows students to develop concrete,
tangible products of the real world that arise from the learners’
imagination. This way, constructionist learning is raised to a level that
enables students to gain haptic experience and thereby concretizes the
virtual. In this paper the defining characteristics of physical computing
are described. Key competences to be gained with physical computing
will be identified.
Mentoring in a Digital World
(2015)
This paper focuses on the results of the evaluation of the first
pilot of an e-mentoring unit designed by the Hands-On ICT consortium,
funded by the EU LLL programme. The overall aim of this two-year
activity is to investigate the value for professional learning of Massive
Online Open Courses (MOOCs) and Community Online Open Courses
(COOCs) in the context of a ‘community of practice’. Three units in the
first pilot covered aspects of using digital technologies to develop creative
thinking skills. The findings in this paper relate to the fourth unit
about e-mentoring, a skill that was important to delivering the course
content in the other three units. Findings about the e-mentoring unit
included: the students’ request for detailed profiles so that participants
can get to know each other; and, the need to reconcile the different
interpretations of e-mentoring held by the participants when the course
begins. The evaluators concluded that the major issues were that: not all
professional learners would self-organise and network; and few would
wish to mentor their colleagues voluntarily. Therefore, the e-mentoring
issues will need careful consideration in pilots two and three to identify
how e-mentoring will be organised.
The study reported in this paper involved the employment
of specific in-class exercises using a Personal Response System (PRS).
These exercises were designed with two goals: to enhance students’
capabilities of tracing a given code and of explaining a given code in
natural language with some abstraction. The paper presents evidence
from the actual use of the PRS along with students’ subjective impressions
regarding both the use of the PRS and the special exercises. The
conclusions from the findings are followed with a short discussion on
benefits of PRS-based mental processing exercises for learning programming
and beyond.
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.
How does the Implementation of a Literacy Learning Tool Kit influence Literacy Skill Acquisition?
(2015)
This study aimed at following how teachers transfer skills
into results while using ABRA literacy software. This was done in
the second part of the pilot study whose aim was to provide equity to
control group teachers and students by exposing them to the ABRACADABRA
treatment after the end of phase 1. This opportunity was
used to follow the phase 1 teachers to see how the skills learned were
being transformed into results. A standard three-day initial training and
planning session on how to use ABRA to teach literacy was held at the
beginning of each phase for ABRA teachers (phase 1 experimental and
phase 2 delayed ABRA). Teachers were provided with teaching materials
including a tentative ABRA curriculum developed to align with the
Kenyan English Language requirements for year 1 and 3 students. Results
showed that although there was no significant difference between
the groups in vocabulary-related subscales which include word reading
and meaning as well as sentence comprehension, students in ABRACADABRA
classes improved their scores at a significantly higher rate
than students in control classes in comprehension related scores. An
average student in the ABRACADABRA group improved by 12 and
16 percentile points respectively compared to their counterparts in the
control group.
The Technology Proficiency Self-Assessment (TPSA) questionnaire
has been used for 15 years in the USA and other nations as a
self-efficacy measure for proficiencies fundamental to effective technology
integration in the classroom learning environment. Internal consistency
reliabilities for each of the five-item scales have typically ranged
from .73 to .88 for preservice or inservice technology-using teachers.
Due to changing technologies used in education, researchers sought to
renovate partially obsolete items and extend self-efficacy assessment to
new areas, such as social media and mobile learning. Analysis of 2014
data gathered on a new, 34 item version of the TPSA indicates that the
four established areas of email, World Wide Web (WWW), integrated
applications, and teaching with technology continue to form consistent
scales with reliabilities ranging from .81 to .93, while the 14 new items
gathered to represent emerging technologies and media separate into
two scales, each with internal consistency reliabilities greater than .9.
The renovated TPSA is deemed to be worthy of continued use in the
teaching with technology context.
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.
How Things Work
(2015)
Recognizing and defining functionality is a key competence
adopted in all kinds of programming projects. This study investigates
how far students without specific informatics training are able to identify
and verbalize functions and parameters. It presents observations
from classroom activities on functional modeling in high school chemistry
lessons with altogether 154 students. Finally it discusses the potential
of functional modelling to improve the comprehension of scientific
content.
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.
This article shows a discussion about the key competencies
in informatics and ICT viewed from a philosophical foundation presented
by Martha Nussbaum, which is known as ‘ten central capabilities’.
Firstly, the outline of ‘The Capability Approach’, which has been presented
by Amartya Sen and Nussbaum as a theoretical framework of
assessing the state of social welfare, will be explained. Secondly, the
body of Nussbaum’s ten central capabilities and the reason for being
applied as the basis of discussion will be shown. Thirdly, the relationship
between the concept of ‘capability’ and ‘competency’ is to be
discussed. After that, the author’s assumption of the key competencies
in informatics and ICT led from the examination of Nussbaum’s ten
capabilities will be presented.
The objectives of this study were to examine (a) the effect
of dynamic assessment (DA) in a 3D Immersive Virtual Reality
(IVR) environment as compared with computerized 2D and noncomputerized
(NC) situations on cognitive modifiability, and (b) the
transfer effects of these conditions on more difficult problem solving
administered two weeks later in a non-computerized environment. A
sample of 117 children aged 6:6-9:0 years were randomly assigned
into three experimental groups of DA conditions: 3D, 2D, and NC, and
one control group (C). All groups received the pre- and post-teaching
Analogies subtest of the Cognitive Modifiability Battery (CMB-AN).
The experimental groups received a teaching phase in conditions similar
to the pre-and post-teaching phases. The findings showed that cognitive
modifiability, in a 3D IVR, was distinctively higher than in the two
other experimental groups (2D computer group and NC group). It was
also found that the 3D group showed significantly higher performance
in transfer problems than the 2D and NC groups.