Ohjelmoinnin opetus peruskoulussa: toiminnallisuutta ja graafista ohjelmointikieltä hyödyntävien opetusmenetelmien vertailu

Ohjelmoinnin opettaminen yleissivistävänä oppiaineena on viime aikoina herättänyt kiinnostusta Suomessa ja muualla maailmassa. Esimerkiksi Suomen opetushallituksen määrittämien, vuonna 2016 käyttöön otettavien peruskoulun opintosuunnitelman perusteiden mukaan, ohjelmointitaitoja aletaan opettaa suomalaisissa peruskouluissa ensimmäiseltä luokalta alkaen. Ohjelmointia ei olla lisäämässä omaksi oppiaineekseen, vaan sen opetuksen on tarkoitus tapahtua muiden oppiaineiden, kuten matematiikan yhteydessä. Tämä tutkimus käsittelee yleissivistävää ohjelmoinnin opetusta yleisesti, käy läpi yleisimpiä haasteita ohjelmoinnin oppimisessa ja tarkastelee erilaisten opetusmenetelmien soveltuvuutta erityisesti nuorten oppilaiden opettamiseen. Tutkimusta varten toteutettiin verkkoympäristössä toimiva, noin 9–12-vuotiaille oppilaille suunnattu graafista ohjelmointikieltä ja visuaalisuutta tehokkaasti hyödyntävä oppimissovellus. Oppimissovelluksen avulla toteutettiin alakoulun neljänsien luokkien kanssa vertailututkimus, jossa graafisella ohjelmointikielellä tapahtuvan opetuksen toimivuutta vertailtiin toiseen opetusmenetelmään, jossa oppilaat tutustuivat ohjelmoinnin perusteisiin toiminnallisten leikkien avulla. Vertailututkimuksessa kahden neljännen luokan oppilaat suorittivat samankaltaisia, ohjelmoinnin peruskäsitteisiin liittyviä ohjelmointitehtäviä molemmilla opetus-menetelmillä. Tutkimuksen tavoitteena oli selvittää alakouluoppilaiden nykyistä ohjelmointiosaamista, sitä minkälaisen vastaanoton ohjelmoinnin opetus alakouluoppilailta saa, onko erilaisilla opetusmenetelmillä merkitystä opetuksen toteutuksen kannalta ja näkyykö eri opetusmenetelmillä opetettujen luokkien oppimistuloksissa eroja. Oppilaat suhtautuivat kumpaankin opetusmenetelmään myönteisesti, ja osoittivat kiinnostusta ohjelmoinnin opiskeluun. Sisällöllisesti oppitunneille oli varattu turhan paljon materiaalia, mutta esimerkiksi yhden keskeisimmän aiheen, eli toiston käsitteen oppimisessa aktiivisilla leikeillä harjoitellut luokka osoitti huomattavasti graafisella ohjelmointikielellä harjoitellutta luokkaa parempaa osaamista oppitunnin jälkeen. Ohjelmakoodin peräkkäisyyteen liittyvä osaaminen oli neljäsluokkalaisilla hyvin hallussa jo ennen ohjelmointiharjoituksia. Aiheeseen liittyvän taustatutkimuksen ja luokkien opettajien haastatteluiden perusteella havaittiin koulujen valmiuksien opetussuunnitelmauudistuksen mukaiseen ohjelmoinnin opettamiseen olevan vielä heikolla tasolla.

Tietokantaratkaisuehdotus pientasajännitesähköverkoston mittausdatavarastoksi

Lappeenrannan teknillinen yliopisto tutkii pientasajännitesähkön käyttöä. Yliopisto on rakennuttanut Järvi-Suomen Energia Oy:n ja Suur-Savon Sähkö Oy:n kanssa yhteistyössä kokeellisen pientasajännitesähköverkon, jolla pystytään tarjoamaan kenttäolosuhteet pienjännitetutkimukselle todellisilla asiakkailla ja todentaa LVDC-teknologiaa ja muita älykkään sähköverkon toimintoja kenttäolosuhteissa. Verkon tasajänniteyhteys on rakennettu 20 kV sähkönjakeluverkon ja neljän kuluttajan välille. 20 kV keskijännite suunnataan tasamuuntamolla ±750 V pientasajännitteeksi ja uudestaan 400/230 V vaihtojännitteeksi kuluttajien läheisyydessä. Tämän kandidaatintyön tarkoituksena on luoda yliopistolle tietokanta pientasajännitesähköverkosta kertyvälle tiedolle ja mittaustuloksille. Tietokanta nähtiin tarpeelliseksi luoda, jotta pienjänniteverkon mittaustuloksia pystytään myöhemmin tarkastelemaan yhdessä ja yhtenäisessä muodossa. Yhdeksi tutkimuskysymykseksi muodostui, kuinka järjestää ja visualisoida kaikki verkosta palvelimille kertyvä mittausdata. Työssä on huomioitu myös kolme tietokantaa mahdollisesti hyödyntävää käyttäjäryhmää: kotitalousasiakkaat, sähköverkkoyhtiöt ja tutkimuslaboratorio, sekä pohdittu tietokannan hyötyä ja merkitystä näille käyttäjille. Toiseksi tutkimuskysymykseksi muodostuikin, mikä kaikesta tietokantaan talletetusta datasta olisi oleellisen tärkeää ottaa talteen näiden asiakkaiden kannalta, ja kuinka nämä voisivat hakea tietoa tietokannasta. Työn tutkimusmenetelmät perustuvat jo valmiiksi olemassa olevaan mittausdataan. Työtä varten on käytetty sekä painettua että sähköisessä muodossa olevaa kirjallisuutta. Työn tuloksena on saatu luotua tietokanta MySQL Workbench -ohjelmistolla, sekä mittausdatan keräys- ja käsittelyohjelmat Python-ohjelmointikielellä. Lisäksi on luotu erillinen MATLAB-rajapinta tiedon visualisoimista varten, jolla havainnollistetaan kolmen asiakasryhmän mittausdataa. Tietokanta ja sen tiedon visualisointi antavat kuluttajalle mahdollisuuden ymmärtää paremmin omaa sähkönkäyttöään, sekä sähköverkkoyhtiöille ja tutkimuslaboratorioille muun muassa tietoa sähkön laadusta ja verkon kuormituksesta.

Online MBPeT dashboard : enabling performance testing as a service in the cloud

In this thesis, tool support is addressed for the combined disciplines of Model-based testing and performance testing. Model-based testing (MBT) utilizes abstract behavioral models to automate test generation, thus decreasing time and cost of test creation. MBT is a functional testing technique, thereby focusing on output, behavior, and functionality. Performance testing, however, is non-functional and is concerned with responsiveness and stability under various load conditions. MBPeT (Model-Based Performance evaluation Tool) is one such tool which utilizes probabilistic models, representing dynamic real-world user behavior patterns, to generate synthetic workload against a System Under Test and in turn carry out performance analysis based on key performance indicators (KPI). Developed at Åbo Akademi University, the MBPeT tool is currently comprised of a downloadable command-line based tool as well as a graphical user interface. The goal of this thesis project is two-fold: 1) to extend the existing MBPeT tool by deploying it as a web-based application, thereby removing the requirement of local installation, and 2) to design a user interface for this web application which will add new user interaction paradigms to the existing feature set of the tool. All phases of the MBPeT process will be realized via this single web deployment location including probabilistic model creation, test configurations, test session execution against a SUT with real-time monitoring of user configurable metric, and final test report generation and display. This web application (MBPeT Dashboard) is implemented with the Java programming language on top of the Vaadin framework for rich internet application development. The Vaadin framework handles the complicated web communications processes and front-end technologies, freeing developers to implement the business logic as well as the user interface in pure Java. A number of experiments are run in a case study environment to validate the functionality of the newly developed Dashboard application as well as the scalability of the solution implemented in handling multiple concurrent users. The results support a successful solution with regards to the functional and performance criteria defined, while improvements and optimizations are suggested to increase both of these factors.

Raspberry Pi-pohjainen dataloggeri

Dataloggerit ovat tärkeitä mittaustekniikassa käytettäviä mittalaitteita, joiden tarkoituksena on kerätä talteen mittausdataa pitkiltä aikaväleiltä. Dataloggereita voidaan käyttää esimerkiksi teollista prosessia osana olevien toimilaitteiden tai kotitalouden energiajärjestelmän seurannassa. Teollisen luokan dataloggerit ovat yleensä hinnaltaan satojen tai tuhansien eurojen luokkaa. Työssä pyrittiin löytämään teollisen luokan laitteille halpa ja helppokäyttöinen vaihtoehto, joka on kuitenkin riittävän tehokas ja toimiva. Työssä suunniteltiin ja toteutettiin dataloggeri Raspberry Pi-alustalle ja testattiin sitä oikeaa teollista ympäristöä vastaavissa olosuhteissa. Kirjallisuudesta ja internet artikkeleista etsittiin samankaltaisia laite- ja ohjelmistoratkaisuja ja niitä käytettiin dataloggausjärjestelmän pohjana. Raspberry Pi-alustalle koodattiin yksinkertainen Python-kielinen data-loggausohjelma, joka käyttää Modbus-tiedonsiirtoprotokollaa. Testien perusteella voidaan todeta, että toteutettu dataloggeri on toimiva ja kykenee kaupallisten dataloggereiden tasoiseen mittaukseen ainakin pienillä näytteistystaajuuksilla. Toteutettu dataloggeri on myös huomattavasti kaupallisia dataloggereita halvempi. Helppokäyttöisyyden näkökulmasta dataloggerissa havaittiin puutteita, joita käydään läpi jatkokehitysideoiden muodossa.

Tool-supported invariant-based programming

The development of correct programs is a core problem in computer science. Although formal verification methods for establishing correctness with mathematical rigor are available, programmers often find these difficult to put into practice. One hurdle is deriving the loop invariants and proving that the code maintains them. So called correct-by-construction methods aim to alleviate this issue by integrating verification into the programming workflow. Invariant-based programming is a practical correct-by-construction method in which the programmer first establishes the invariant structure, and then incrementally extends the program in steps of adding code and proving after each addition that the code is consistent with the invariants. In this way, the program is kept internally consistent throughout its development, and the construction of the correctness arguments (proofs) becomes an integral part of the programming workflow. A characteristic of the approach is that programs are described as invariant diagrams, a graphical notation similar to the state charts familiar to programmers. Invariant-based programming is a new method that has not been evaluated in large scale studies yet. The most important prerequisite for feasibility on a larger scale is a high degree of automation. The goal of the Socos project has been to build tools to assist the construction and verification of programs using the method. This thesis describes the implementation and evaluation of a prototype tool in the context of the Socos project. The tool supports the drawing of the diagrams, automatic derivation and discharging of verification conditions, and interactive proofs. It is used to develop programs that are correct by construction. The tool consists of a diagrammatic environment connected to a verification condition generator and an existing state-of-the-art theorem prover. Its core is a semantics for translating diagrams into verification conditions, which are sent to the underlying theorem prover. We describe a concrete method for 1) deriving sufficient conditions for total correctness of an invariant diagram; 2) sending the conditions to the theorem prover for simplification; and 3) reporting the results of the simplification to the programmer in a way that is consistent with the invariantbased programming workflow and that allows errors in the program specification to be efficiently detected. The tool uses an efficient automatic proof strategy to prove as many conditions as possible automatically and lets the remaining conditions be proved interactively. The tool is based on the verification system PVS and i uses the SMT (Satisfiability Modulo Theories) solver Yices as a catch-all decision procedure. Conditions that were not discharged automatically may be proved interactively using the PVS proof assistant. The programming workflow is very similar to the process by which a mathematical theory is developed inside a computer supported theorem prover environment such as PVS. The programmer reduces a large verification problem with the aid of the tool into a set of smaller problems (lemmas), and he can substantially improve the degree of proof automation by developing specialized background theories and proof strategies to support the specification and verification of a specific class of programs. We demonstrate this workflow by describing in detail the construction of a verified sorting algorithm. Tool-supported verification often has little to no presence in computer science (CS) curricula. Furthermore, program verification is frequently introduced as an advanced and purely theoretical topic that is not connected to the workflow taught in the early and practically oriented programming courses. Our hypothesis is that verification could be introduced early in the CS education, and that verification tools could be used in the classroom to support the teaching of formal methods. A prototype of Socos has been used in a course at Åbo Akademi University targeted at first and second year undergraduate students. We evaluate the use of Socos in the course as part of a case study carried out in 2007.

Neural correlates of language learning in adults

The human language-learning ability persists throughout life, indicating considerable flexibility at the cognitive and neural level. This ability spans from expanding the vocabulary in the mother tongue to acquisition of a new language with its lexicon and grammar. The present thesis consists of five studies that tap both of these aspects of adult language learning by using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) during language processing and language learning tasks. The thesis shows that learning novel phonological word forms, either in the native tongue or when exposed to a foreign phonology, activates the brain in similar ways. The results also show that novel native words readily become integrated in the mental lexicon. Several studies in the thesis highlight the left temporal cortex as an important brain region in learning and accessing phonological forms. Incidental learning of foreign phonological word forms was reflected in functionally distinct temporal lobe areas that, respectively, reflected short-term memory processes and more stable learning that persisted to the next day. In a study where explicitly trained items were tracked for ten months, it was found that enhanced naming-related temporal and frontal activation one week after learning was predictive of good long-term memory. The results suggest that memory maintenance is an active process that depends on mechanisms of reconsolidation, and that these process vary considerably between individuals. The thesis put special emphasis on studying language learning in the context of language production. The neural foundation of language production has been studied considerably less than that of perceptive language, especially on the sentence level. A well-known paradigm in language production studies is picture naming, also used as a clinical tool in neuropsychology. This thesis shows that accessing the meaning and phonological form of a depicted object are subserved by different neural implementations. Moreover, a comparison between action and object naming from identical images indicated that the grammatical class of the retrieved word (verb, noun) is less important than the visual content of the image. In the present thesis, the picture naming was further modified into a novel paradigm in order to probe sentence-level speech production in a newly learned miniature language. Neural activity related to grammatical processing did not differ between the novel language and the mother tongue, but stronger neural activation for the novel language was observed during the planning of the upcoming output, likely related to more demanding lexical retrieval and short-term memory. In sum, the thesis aimed at examining language learning by combining different linguistic domains, such as phonology, semantics, and grammar, in a dynamic description of language processing in the human brain.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.