Complementing ICT Studies with Learning Objects on Domain Ontologies

Tarmo Robal, Helena Kruus, Ahto Kalja Department of Computer Engineering, Tallinn University of Technology

Akadeemia 15a, 12618 Tallinn, Estonia 1tarmo.robal@ati.ttu.ee 2helena.kruus@ati.ttu.ee

3ahto@cs.ioc.ee

Abstract— Today, information and communication technology (ICT) plays a crucial role in our lives. Devices taking advantage of the rapid development of ICT are increasingly used to ease and provide comfort to our daily activities. This has also affected the way young engineers prefer to learn and how they are taught. Traditional methods, proven to work, may not be so attractive to students anymore, in comparison to all the widgets, apps and knowledge in various forms available over the Internet. To make courses and topics more attractive, young system engineers need to be educated taking advantage of the rapid development of technologies young are accustomed to use, including e-learning and interactive tools to assure their good skills and increased interest towards studies. Intelligent learning objects clearly demonstrating a topic area and allowing students to explore problem domain without restrictions in time and space will provide support for any type of course, enliven studies, and clearly serve the goal formulated hereinbefore. Keywords— Interactive learning objects, ontology, digital logic, online education, educational tools

I. INTRODUCTION Our society has become largely dependent on information

and communication technology (ICT) and various computer-based systems. Devices equipped with sophisticated microelectronic systems and corresponding software can be found everywhere – from smartphones and personal music players to kitchenware. Despite the complexity of these systems, they are composed of simple logic gates. The rapid development and shift to mass-usage of electronics has introduced a dependency on such devices and a risk of vulnerability in case of system failures. Nevertheless, this risk is neglected and gets attention usually only in case of system failures – otherwise such breakdowns would not have had dramatic effect on our lives. For example, a bug in smartphone software may frustrate masses of people but does not cause a threat to society. A failure in an aircraft control system or in a nuclear power plant management system however may have fatal consequences.

Obviously, if young system engineers are educated with great care from the beginning, using different teaching methods, including e-learning and interactive tools made available by the rapid development of the Internet and its associated technologies, their good skills and increased

interest towards study field can be assured. Thereby, proper education of future engineers can mitigate some of the risks concerned with computer systems development.

The rapid development of the Internet and its associated technologies, including technologies for the semantic web, has enabled web-based training and distance learning to become a reality and made it possible to move studies fully or partially into virtual learning environments. This progress has also enabled creation of digital learning objects, varying from simple textual content to images, animations and interactive simulator tools. A learning object, as defined by the IEEE, is any entity – digital or non-digital – that may be used for learning, education or training [1]. Clearly, digital learning objects as interactive hands-on tools and web enabled learning management systems (LMS) are taking education to the next level and pose new challenges for teaching, as users can access such systems everywhere and any time where the Internet is present, regardless whether they are at home, in office, sitting in the park with tablet PC or smart-phone, and so forth. This rapid evolution of web technologies has now enabled to develop learning management systems with various functionalities on an affordable level on different platforms.

In this paper we discuss the need for establishing interactive learning objects, explore students’ opinions and present an intelligent learning object on domain ontology as a tool for teaching the basics of digital logic (DL) in which students learn by exploring and investigating elements of DL. The tool aims to solve some of the problems students have highlighted regarding learning basics of digital logic during their early studies. The rest of the paper is structured as follows: Section II provides an overview of teaching digital logic, Section III describes the learning object based on domain knowledge, and Section IV draws conclusions.

II. TEACHING THE BASICS OF DIGITAL LOGIC With the evolvement of technology, microelectronic

systems are becoming more complex, introducing design and testability issues as one of the major components of manufacturing costs of a product. Hardware consists of a few simple building blocks – logic gates, which are constructed using the fundamental devices – transistors. Students have to understand how the basic elements of digital logic (DL), such

as AND-, OR-, etc. gates, are working, in order to be able to compose complex systems of these basic elements. This is a competence they need to acquire before moving on to next level with their studies in becoming an experienced engineer.

At Tallinn University of Technology (TUT) such engineers are mainly educated under the curricula of Computer Systems, holding a number of hardware design and test related courses. Educating students with solid knowledge of the basics of DL as early as possible (starting on the first year) is vital when expecting them to be able to evaluate behavior of gates and compose tests for fault detecting in larger combinational schemas at signal level at later courses.

At TUT the basics of DL are taught (course Computers I) to all the students of the Faculty of Information Technology as a part of basic studies regardless of their curricula. However, dependent on the curricula, students have different technical background, which may or may not contribute to their studies. For instance, for students of the Business Information Technology curricula, learning the basics of DL can be quite troublesome as their main study objective is in between economy and ICT. Thereby, interactive presentation of domain knowledge as some sort of an intelligent learning object can alleviate the problem and broaden their background knowledge.

A. Need for Interactive Environments and Intelligent Tools Teaching digital systems and logic is a complex area,

where explanations should be accompanied by tools which clearly demonstrate static knowledge in dynamic form. Traditionally, students visit lectures, make notes and have some practical tasks to perform. The knowledge from the lectures is mainly reflected by course materials and students’ notes, which are in a “lifeless” form. The motivation to learn from such materials may not be so high for today’s technology-aware students. They rather prefer interactive learning, game-like simulator tools, videos, widgets and gadgets, etc. everything they can do online. For instance, our students tend to rely on Wikipedia and Google, Facebook posts, and even seek information on a video sharing website YouTube. Yet, there is no guarantee on information correctness for these resources, meaning these resources may contain misunderstandings as well as errors, although one can find excellent learning objects there as well. But still the question, whether students’ level of knowledge is sufficient enough to evaluate these resources, remains open. Lack of curiosity towards traditional approach, trend of ignoring the need to continually keep up with course materials and trying to rely on “more interesting sources of knowledge” adheres to insufficiency of theoretical knowledge clearly seen during practical labs, where students do not recognize basic elements, mix up their behavior or make other mistakes because of this. Hence, the motivation to learn from traditional materials is low, creating a need to find new ways to educate and raise motivation in students.

We see the remedy in interactive environments, proper hands-on “technical toys” as tools, where students can easily explore the problem domain by experimenting and playing through certain learning scenarios or explore knowledge

through a set of exercises. Obviously, such tools must be generally available via the Internet and applicable for classroom, campus and off-campus use. Such learning objects support developing creativity and skills of problem solving in teaching-learning process – the ability future engineers need the most.

Previously, we have introduced a framework on interactive hands-on tools as learning objects on web services, developed a web service and interactive tools to introduce fundamental elements of digital logic with their behavior [2]. To provide students a comprehensive tool on the topics of basic digital logic gates, and help them better understand the domain knowledge, we have initiated a project to develop an interactive and intelligent learning object on domain ontology. The knowledge needs to be taught easily and rapidly, so that an interest towards the topics rises in students, rather than declines. If we succeed to initiate this curiosity, students are more than willing to explore any additional materials on their own and get on with problem solving.

B. What do Students Say? Before continuing the discussion on the intelligent learning

object, let us have a look at what students think about their studies of microelectronics at TUT. We interviewed in an informal atmosphere a small group of second and third year students who already had passed the course Computers I, asking them what were the typical issues they had struggled with while learning the basics of DL; what kind of information they would have liked to have at that their hand at that moment (in a standardized way) about every gate; what relationships between the elements they had considered to be important; where had they searched for knowledge while being in trouble, etc. From the interviews we concluded the following:

Firstly, there is a problem in comprehending why learning digital logic is needed, what it gives to the students in the future, and how it connects up to already learned things. For instance, basics of DL (course Computers I) is also taught for students of the Informatics curricula, who are specializing on software engineering. This is mainly a motivational issue, which cannot be directly addressed by any interactive environment; however learning can be made more attractive and challenging.

Secondly, there is a set of questions students are struggling with while learning basic digital logic gates. Even though course materials cover most of them, they are in a “lifeless” form and not usually accompanied by students’ notes from the lectures, thus they are not complete and not adapted to a particular student because of the missing notes. This tendency of students not taking notes and believing that they can rely only on materials distributed by lecturer is distressing. These materials are not interesting for the young, raising the following issues:

Existential questions: What elements do exist? How many inputs do they have and what is the output? What does each of the gates actually do? Is this behavior somehow known to me from any other field/course?

What is this element alike to? How are they built up? Why are they needed?

Usability related questions: Where can I use them? What circuits or basic elements can I compose using the available gate-set?

Technical and other questions: What is the size of the gate? What is the price for this element? How long is the gate delay? What are the technologies used to implement the gates?

We also asked the interviewed students about their opinion on having an intelligent system to address all the problems they had just outlined. The idea was welcomed with some remarks for serious requirements, such as it needs to be web based or web enabled, well-advertised during the course, so that everybody would get the information of such a tool existing, easily accessible and usable, and applicable everywhere, especially campus-wide and at home.

The conducted interviews provided us a set of questions to tackle. Obviously, with an intelligent system addressing all the questions students raised, the motivation to learn would increase. This on the other hand created a question how to achieve such a tool.

III. A TEACHING TOOLS BASED ON DOMAIN KNOWLEDGE

A. Why Ontology? One of the best ways to describe and store domain

knowledge today is using ontologies. An ontology is an explicit specification of conceptualization, it represents domain knowledge and makes it possible to reuse the latter [3], [4]. Ontologies are an important part of any intelligent system. They provide a formal presentation of knowledge as a set of concepts within a domain, and the relationships between those concepts, allowing to reason about the entities within that domain. Hence, they enable a shared vocabulary for modeling a domain by describing the type of concepts that exist, and their properties and relations.

By describing knowledge about basic DL gates in ontology, we give it a formal presentation and make it machine-processable. This provides an organized structure of the domain concepts, and their relationships, on which reasoning facilities can be run on. The latter helps to keep the ontology structure simple and clear, and most importantly maintainable. In addition to the aforementioned advantages, we outline extendibility as the third benefit gained. New knowledge (concepts and their properties (in ontological sense relationships)) can be added whenever needed, resulting in more precise description of the domain, and if exploited as a core component in an intelligent interactive learning object, this information gets automatically presented to students seeking for knowledge.

To the best of our knowledge, there is no publicly available ontology for digital logic domain describing basic logic gates and relationships between them. Therefore, we had to construct the ontology from the beginning.

B. Design of the DL Ontology We constructed the ontology for the intelligent interactive

DL learning tool manually using the Protégé 4.1 ontology editor [5]. The ontology is represented in the Web Ontology Language (OWL) [6] recommended by the World Wide Web Consortium (W3C) as a standard language for ontology representation. OWL is capable to capture knowledge by representing the concepts and relationships among concepts of a given domain and therefore is suitable for knowledge representation as well as for automated reasoning.

Our ontology of digital logic (Fig. 1) contains predefined primitive concepts (classes) for describing basic logic gates (e.g., concept “AND_Gate”), implementation technologies for DL gates (e.g., concept “TTL”), as well as more sophisticated constructs of digital logic. It also contains concepts describing characteristics of basic gates. Besides primitive classes, defined concepts, which hold only a definition of the class, are used. The class hierarchy for defined concepts is automatically computed by a reasoner (we have used the Pellet OWL 2 reasoner [7]) into a subclass-superclass relationship in an inferred ontology. For instance, after reasoning is carried out, the defined concept “ElementsImplementedIn-NMOSTechnology” holds a subclass “AND_Gate”.

Fig.1 Established domain ontology for teaching the basics of digital logics (screenshot from the Protégé 4 ontology editor). The concept “AND-Gate” is selected (on the left) and definitions shown (right pane)

The actual gates used for modeling and simulation in laboratory works are also present in the ontology and modeled as individuals of the gate concepts. They have all the characteristics described for the concepts they belong to and attributes that distinguish them from each-other. For example, we can find an individual “ind_4x2NAND” belonging to class “NAND_Gate”, having a property value “hasPartNumber” equal to 7400, returned value type “inverted”, number of inputs equal to 2, etc. in the ontology. Using reasoning facilities, we get to know their membership to other classes defined in the ontology, which is a great effort attained.

Each element in the ontology is annotated, i.e., concepts, properties and individuals are equipped with name, description, comments, etc. The annotations can also hold instructors comments and remarks, which comes especially useful with individuals representing gates from real world.

The relationships between concepts are represented using OWL properties. We have used both, object and data

properties to describe various characteristics of DL gates, such as implementation technology, number of inputs and outputs, output type, constructability, graphical notation, truth table resource, element part number, delay, frequency range, power consumption, supply voltage, etc.

Thus, the amount of information captured by ontology to be presented in an intelligent learning object for teaching basics of DL is fairly large, covering most of the aspects. While designing the ontology, we also considered the students opinions revealed during the interviews.

C. Intelligent Learning Object on Domain Ontology Having discussed teaching problems, needs and opinions of

students, and the main core component of the interactive learning tool – the DL ontology, let us now have a look at the interactive intelligent learning object itself.

The intelligent learning object is based on a specially designed domain ontology capturing knowledge by a set of concepts within the domain of digital microelectronics and the relationships between those concepts. The tool is meant for the course Computers I during which the first year students are educated in the field of IC technologies, combinational circuits and special hardware. The course sets up all the necessary prerequisites for understanding the basics of DL, knowledge needed in further courses on issues of design and test. For advanced level courses, we already have a set of interactive tools for special SoC and NoC design in test related topics [8], [9].

The graphical user interface (GUI) of the learning object prototype tool is divided into main tabs such as Gate explorer, Elements library and Technologies. In the gate explorer view students can select an element of DL (e.g. OR, AND, MUX, DEC, etc.) from the list of available gates in the ontology. Presently, the set of elements includes simple gates but it is not limited as the ontology is expandable. After gate selection, the ontology is queried and domain knowledge represented. Fig. 2 shows the system architecture for the prototype tool and GUI after selecting OR-gate. We can see different page sections providing description, graphical notation (ANSI and IEC), truth table, general technical details, related elements library and formation possibilities for the element.

The right bottom corner includes an ‘Explore and Test your knowledge’ section, which is driven by the e-EDU WSI web service described in [2]. This section provides two modes of learning: either the student sets input signal values with the maximum length of 24 bits in a signal sequence and lets the service calculate the output bit-stream, or the student also sets the proposed output and tests his/her knowledge. Different sections on the GUI are equipped with help information (?-marks in a round) as needed, also originating from the ontology.

The Technologies tab displays information about gate implementation technologies and through ontology reasoning also the set of elements under each of the technology. The Elements library tab shows a list of real gates (individuals of DL ontology concepts) and their properties.

Thus, the tool enables students easy access to information about elements of digital logic, and acts as a useful assistant

while performing exercises in labs, for instance in a CAD environment. An example case could be as follows: a student needs to place an OR-gate on the schema. He/she opens the tool, looks up the gate, gets a list of all the available elements, seeing that a part 7432 (4x2OR) with four OR-gates on a single chip is suitable to solve the task.

The described learning object is presently implemented in Java language as an applet, due to the fact that the majority of tools available for dealing with ontologies, including the OWL API [10], are Java based. Using Java has the advantage of being platform independent and thus available for Windows, Linux/UNIX, and Mac OS platforms. However, our future development plans include the realization of a web-based interface for the learning object, where Java has only the role of middleware. Transforming the tool to be a web-enabled learning object would also deliver the advantage that users would not need to install additional plug-ins anymore to use the tool.

As shown, the tool serves the underlying idea of intelligent learning object, provides key points in theory and illustration of basic principles of DL gates using graphical representation of the learning object and a platform independent user-friendly interface with easy access to dynamic content in a game-like tool for learning by doing.

Java GUI

Domain OntologyOWL2

Reasoner

Web Servicese-EDU WSI DL Service

RepositoryFiles &

Resources

OWL APIJava

Middleware LayerJava

Middleware Layer

Learners

Fig. 2 System architecture for the learning object on domain ontology to support the learning-teaching process of basics of digital logic. Also, graphical user interface, where students can explore elements of DL, is shown

D. Educational Goals Targeted The use of computers in learning-teaching process brings

many advantages. Firstly, it enables to individualize learning as students are able to explore knowledge on their own and repeat learning scenarios as necessary. Secondly, interactive learning objects allow to explain things more easily with animation and running examples than amounts of textbook material. Thirdly, the usage of such learning objects is not restricted to time and space.

The main didactic aim of our learning object is set on teaching perception of the basics of digital logic, described from various aspects, illustrated with gates behavior, notations, truth tables, and relevant details. The use of a specially designed DL ontology adds machine-processable knowledge providing higher degree of description for elements in the tool. Our intelligent learning object as an educational tool targets the following goals:

Provide overview and description of basic DL gates, their behavior, related properties (i.e., delays, chips and technologies available, etc.), and the relationships between those elements;

Raise interest towards studies and enliven learning-teaching process by a “game-like” tool to explore available knowledge about DL;

Support and motivate students to learn independently through the concept of “learn by doing”;

Enable an environment to self-test obtained knowledge and if needed refresh it before taking practical tasks in labs, i.e., pre-check of necessary knowledge level;

A possibility for instructors to add comments on real digital gates (modeled as individuals in the ontology) to assist students during the labs, for instance with common mistakes or misuse;

Compose various exercises students can solve using the tool, and by this use mental work to reinforce knowledge level.

IV. CONCLUSIONS In this paper we have proposed a framework for and

provided an overview of establishing learning objects on domain ontologies. Advantages gained from using domain ontologies as core components of learning objects are highlighted together with educational goals targeted by the prototype tool for teaching the basics of digital logic.

The presented intelligent learning object for teaching the basics of digital logic allows students to explore domain

knowledge in a game-like hands-on tool and helps them to get solid knowledge necessary for advanced level courses on microelectronics. The tool, which incorporates specially designed domain ontology as a core component to achieve its goals, supports studies on and off campus, directly in classroom, or for distance computer-aided learning.

Living the era, where microelectronic systems are an integral part of our lives, has produced a need to educate future system engineers using various approaches, including interactive and intelligent tools, to raise their motivation, assure good skills, encourage critical thinking and prepare them being creative engineers in their forthcoming career.

ACKNOWLEDGMENT This work was partially supported by the European

Regional Development Fund (ERDF), the Estonian Center of Excellence in Integrated Electronic Systems and Biomedical Engineering (CEBE) through ERDF, Estonian higher education information and communications technology and research and development activities state program IKTP through ERDF, and by the Estonian Information Technology Foundation higher educational support program Tiger University.

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