Keywords

1 Introduction

The “smart university” (SmU) concept and several related concepts, such as smart classrooms [1,2,3,4,5,6,7,8,9,10,11], smart learning environments [12, 13], smart campus [14,15,16,17], smart education [18,19,20,21,22,23], and smart e-learning [22,23,24], were introduced just several years ago; they are in permanent evolution and improvement since that time. The introduced ideas and approaches to build SmU, as well as smart education (SmE), are rapidly gaining popularity among the leading universities in the world because modern, sophisticated high-tech-based smart technologies, systems, and devices create unique and unprecedented opportunities for academic and training organizations in terms of higher teaching standards and expected learning/training outcomes. “The analysts forecast the global smart education market to grow at a CAGR of 15.45% during the period 2016–2020” [25]. “Markets and Markets forecasts the global smart education and learning market to grow from $193.24 Billion in 2016 to $586.04 Billion in 2021, at a Compound Annual Growth Rate (CAGR) of 24.84%” [26].

1.1 Literature Review

To-date, most researchers are focused on perspectives of contemporary higher education and tendencies that correspond to the concepts of SmU and SmE. For example, the authors of [27,28,29] discuss various aspects of contemporary universities and their future perspectives in the context of applications of smart information and communication technologies (ICT) in education. On the other hand, the authors of [30] presented one of the first research studies on new opportunities for universities in the context of smart education.

The other significant part of research in SmE is focused on the problem of educational outcomes in the contemporary educational systems—smart learning environments (SLE). For example, the concept of outcomes-based education has been proposed and this approach can be regarded as a part of the SmE concept. The main part of obtained outcomes includes the studies of cognitive abilities, needs, skills, and their training through e-learning or, in general, to 21st century skills [31]. There are also resources available on instructional design and cognitive science, which consider the problem of learning, structuring material, communication, and forming cognitive competence in this group, for example [32].

Different attempts to make conceptual models of ICT infrastructure of SmU and smart e-learning systems are currently being actively researched; for example, the topics concerning smart e-learning standards, smart gadgets, and learning equipment are discussed [33]. Several research projects were aimed at organizational aspects of SmU, smart education such as organizational structure, educational trajectories, learning strategies, etc. These projects usually emphasize the fact that many aspects of contemporary education need new flexible organizational structures, which can be referred to as “smart” [30, 34].

The detailed literature review on existing approaches to build SmU is available in another chapter of this book, specifically in [35].

Despite the obvious progress in SmU area, the main concepts and conceptual models of smart universities are not clarified in full yet due to obvious uniqueness, innovativeness, and complexity of this research area.

1.2 Research Project Goal and Objectives

The performed analysis of above-mentioned and multiple additional publications and reports relevant to (1) smart universities, (2) university-wide smart software and hardware systems and technologies, (3) smart classrooms, 94) smart learning environments, and (5) smart educational systems, undoubtedly shows that SmU-related topics will be in the focus of multiple research, design, and development projects in the upcoming 5–10 years. It is expected that, in the near future, SmU concepts and hardware/software/technological solutions will start to play a significant role and be actively deployed and used by leading academic intuitions in the world.

Project Goal. The overall goal of this ongoing multi-aspect research project is to develop conceptual modeling of a smart university, i.e. to identify and classify SmU’s main smart features, components, relations (links) between components, interfaces, inputs, outputs, and limits/constraints. The premise is that SmU conceptual modeling will (1) enable us to identify and predict the most effective software, hardware, pedagogy, teaching/learning activities, services, etc., for the next generation of a university—smart university—and (2) help traditional universities understand the strengths, weaknesses, opportunities, and threats of becoming a smart university and also identify and evaluate paths for a possible transformation from traditional university into a smart one.

Project Objectives. The objectives of this project were to identify SmU’s main (1) smartness levels (or smart features), (2) components, and (3) specific software and hardware systems that go well beyond those in a traditional university with predominantly face-to-face classes and learning activities. Due to limited space, we present a summary of up-to-date research outcomes below.

2 Smart University: Conceptual Modeling

2.1 Smartness University: Modeling of Smartness Levels

Based on our vision of SmU and up-to-date obtained research outcomes, we believe that SmU as a smart system should significantly emphasize, not only pioneering software/hardware features and innovative modern teaching/learning strategies, but also “smart” features of smart systems (Table 3.1) [36, 37]. Therefore, the designers of SmU should pay more attention to a maturity of smart features of SmU that may occur on various levels of SmU’s smartness—smartness levels.

Table 3.1 Classification of smartness levels of a smart system [36, 37]
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Several examples of SmU possible distinctive functions for every proposed SmU smartness level are presented in Table 3.2.

Table 3.2 SmU distinctive features (that go well beyond features of a traditional university) [38]
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2.2 Smartness University: Conceptual Model

The proposed conceptual model of a SmU, labeled as CM-SmU, can be described as follows [40].

Definition 3.1

Smart University is described as n-tuple of n elements that can be chosen from the following main sets:

$$ \begin{aligned} & CM - SmU = < \left\{ {{\text{SmU}}\_{\text{FEATURES}}} \right\}, \, \left\{ {{\text{SmU}}\_{\text{STAKEHOLDERS}}} \right\}, \\ & \quad \quad \quad \quad \quad \quad \left\{ {{\text{SmU}}\_{\text{CURRICULA}}} \right\}, \, \left\{ {{\text{SmU}}\_{\text{PEDAGOGY}}} \right\}, \\ & \quad \quad \quad \quad \quad \quad \left\{ {{\text{SmU}}\_{\text{CLASSROOMS}}} \right\}, \\ & \quad \quad \quad \quad \quad \quad \left\{ {{\text{SmU}}\_{\text{SOFTWARE}}} \right\}, \\ & \quad \quad \quad \quad \quad \quad \left\{ {{\text{SmU}}\_{\text{HARDWARE}}} \right\}, \, \left\{ {{\text{SmU}}\_{\text{TECHNOLOGY}}} \right\}, \\ & \quad \quad \quad \quad \quad \quad \left\{ {{\text{SmU}}\_{\text{RESOURCES}}} \right\} \, > \\ \end{aligned} $$
(3.1)

where:

SmU_FEATURES:

a set of most important smart features of SmU, including adaptation, sensing, inferring, self-learning, anticipation, self-optimization or re-structuring;

SmU_STAKEHOLDERS:

a set of SmU stakeholders; for example, it includes a subset of SmU faculty (instructors) at SmU, i.e. those who are trained and predominantly teach classes in smart classrooms and actively use smart boards, smart systems, smart technology, etc.,

SmU_CURRICULA:

a set of smart programs of study and smart courses at SmU—those that can, for example, change (or optimize) its structure or mode of learning content delivery in accordance with given or identified requirements (due to various types of students or learners);

SmU_PEDAGOGY:

a set of modern pedagogical styles (strategies) to be used at SmU;

SmU_CLASSROOMS:

a set of smart classrooms, smart labs, smart departments and smart offices at SmU;

SmU_SOFTWARE:

a set of university-wide distinctive smart software systems at SmU (i.e. those that go well beyond those used at a traditional university);

SmU_HARDWARE:

a set of university-wide smart hardware systems, devices, equipment and smart technologies used at SmU (i.e. those that go well beyond those used at a traditional university);

SmU_TECHNOLOGY:

a set of university-wide smart technologies to facilitate main functions and features of SmU;

SmU_RESOURCES:

a set of various resources of SmU (financial, technological, human, etc.)

In general, SmUs may have multiple additional minor sets; however, for the purpose of this research project, we will limit a number of SmU most important sets as presented in (3.1).

2.3 Smart University: Modeling Distinctive Components and Elements

SmU may have numerous components of a traditional university; however, it must have multiple additional components to implement actively use and maintain SmU distinctive features that are described in Table 3.2. Based on our vision of SmU and outcomes of our research, the SmU main sets should include at least those set elements (or SmU distinctive sub-components) that are described in Table 3.3.

Table 3.3 SmU main sets (components) and main distinctive sub-sets (sub-components) that go well beyond components of a traditional university
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2.4 Smart University: “Components and Features” Matrix

The performed research enabled us to arrive with a very important outcome—“Smart University: Components and Smartness Levels” matrix (Fig. 3.1). This matrix clearly shows that there should be a one-to-one correspondence between a particular SmU component and SmU smartness levels. The designers of SmU should clearly understand, for example, how to-be-deployed software systems will help SmU to

Fig. 3.1
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“Smart University: Components and Features” matrix

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  1. (1)

    adapt (for example, (a) to smoothly accommodate remote students or students with disabilities in a smart classroom, (b) to various modes of teaching, (c) to various types of learning content delivery and types of courses, etc.),

  2. (2)

    sense (for example, (a) to get data about various activities or processes in a smart classroom or on smart campus, (b) to get data about student learning activities and academic performance, etc.),

  3. (3)

    infer (i.e. process the obtained data, run learning analytics systems, and generate well-thought conclusions or recommendations based on big data analytics)

  4. (4)

    self-learn (for example, to deploy innovative types of teaching and learning strategies or to offer classes on innovative topics that are in high demand in industry),

  5. (5)

    anticipate (for example, to monitor as may areas on campus or inside buildings as possible, and predict and prevent any potentially bad events), and

  6. (6)

    self-optimize (for example, to minimize consumption of electricity/heat in university classrooms and labs during night time and weekends, etc.).

Due to the limits of this chapter, it is impossible to provide details on all obtained research outcomes and findings regarding smart software systems, smart hardware, smart technology, and smart pedagogy; therefore, below we will focus on outcomes of detailed analysis of several important types of software systems for SmU.

3 Smart University: Software Systems’ Design

Based on our vision of SmU, we believe that SmUs should deploy various types of distinctive software systems; a comprehensive list of corresponding software systems is presented in Table 3.3 above. As a part of this research project, for several most important classes of selected software systems to be deployed by SmU, the research team

  1. (1)

    identified a list of desired functions (functionality) of those systems from SmU stakeholders’ point of view;

  2. (2)

    identified, downloaded, and analyzed approximately 10 to 20 existing software systems of designated type—usually including both open source and commercial systems—by means of (a) review of system’s functions and features, (b) review of system’s demo version or trial version, (c) installation and testing of actual system, and d) review of user and analysts’ feedback;

  3. (3)

    identified a list of main functions of system of designated type—i.e., functions to be beneficial for SmU stakeholders, and

  4. (4)

    evaluated and ranked those systems.

A brief summary of our research outcomes for selected classes of software systems for SmUs is presented in multiple tables below, including

  1. (1)

    pre-class learning content development systems for SmU (Tables 3.4, 3.5, 3.6 and 3.7);

    Table 3.4 Pre-class learning content development systems for smart university: A list of system’s desired features
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    Table 3.5 Pre-class learning content development systems for smart university: A list of analyzed systems
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    Table 3.6 Pre-class learning content development systems for smart university: A list of most important features in existing systems
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    Table 3.7 Pre-class learning content development systems for smart university: A list of recommended systems
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  2. (2)

    in-class activities recording systems for SmU (Tables 3.8, 3.9, 3.10 and 11);

    Table 3.8 In-class activities recording systems for smart university: A list of system’s desired features
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    Table 3.9 In-class activities recording systems for smart university: A list of analyzed systems
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    Table 3.10 In-class activities recording systems for smart university: A list of most important features in existing systems
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    Table 3.11 In-class activities recording systems for smart university: A list of recommended systems
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  3. (3)

    post-class activities’ supporting systems for SmU (Tables 3.12, 3.13, 3.14 and 3.15);

    Table 3.12 Post-class activities supporting systems for smart university: A list of system’s desired features
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    Table 3.13 Post-class activities supporting systems for smart university: A list of analyzed systems
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    Table 3.14 Post-class activities supporting systems for smart university: A list of most important features in existing systems
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    Table 3.15 Post-class activities supporting systems for smart university: A list of recommended systems
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  4. (4)

    Web-based audio- and video-conferencing systems for SmU (Tables 3.16, 3.17, 3.18 and 3.19);

    Table 3.16 Web-based audio- and video-conferencing systems for smart university: A list of system’s desired features
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    Table 3.17 Web-based audio- and video-conferencing systems for smart university: A list of analyzed systems
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    Table 3.18 Web-based audio- and video-conferencing systems for smart university: A list of most important features in existing systems
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    Table 3.19 Web-based audio- and video-conferencing systems for smart university: A list of recommended systems
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  5. (5)

    collaborative learning systems for SmU (Tables 3.20, 3.21, 3.22 and 3.23);

    Table 3.20 Collaborative learning systems for smart university: A list of system’s desired features
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    Table 3.21 Collaborative learning systems for smart university: A list of analyzed systems
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    Table 3.22 Collaborative learning systems for smart university: A list of most important features in existing systems
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    Table 3.23 Collaborative learning systems for smart university: A list of recommended systems
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  6. (6)

    context awareness systems for SmU (Tables 3.24, 3.25, 3.26 and 3.27).

    Table 3.24 Context awareness systems for smart university: A list of system’s desired features
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    Table 3.25 Context awareness systems for smart university: A list of analyzed systems
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    Table 3.26 Context awareness systems for smart university: A list of most important features in existing systems
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    Table 3.27 Context awareness systems for smart university: A list of recommended systems
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Additionally, a summary of our research outcomes and findings for software systems, which are focused on students with disabilities at SmU, is presented in [41]. Those software systems include (a) voice-to-text (voice recognition) systems, (b) text-to-voice (voice synthesis) systems, and (c) gesture and motion recognition systems.

3.1 Smartness University: Pre-class Learning Content Development Systems

A brief summary of our research outcomes for pre-class learning content development systems for SmU is presented in Tables 3.4, 3.5, 3.6 and 3.7.

3.2 In-class Activities Recording Systems

A brief summary of our research outcomes for in-class activities recording systems for SmU is presented in Tables 3.8, 3.9, 3.10 and 3.11.

3.3 Post-class Activities’ Supporting Systems

A brief summary of our research outcomes for post-class activities’ supporting systems for SmU is presented in Tables 3.12, 3.13, 3.14 and 3.15.

3.4 Web-Based Audio- and Video-Conferencing Systems

A brief summary of our research outcomes for Web-based audio and video-conferencing systems for SmU is presented in Tables 3.16, 3.17, 3.18 and 3.19.

3.5 Collaborative Learning Systems for Smart University

A brief summary of our research outcomes for collaborative learning systems for SmU is presented in Tables 3.20, 3.21, 3.22 and 3.23.

3.6 Context Awareness Systems for Smart University

In the general case, there may be multiple types of context awareness systems to be used by SmU; they primarily deal with user’s awareness of (a) learning environment, (b) learning process, (c) location on campus or inside a building, (d) safety or security inside a building or on campus, etc. As a result, it is almost impossible to integrate all types of desired user “awareness” in one system. However, below we provide (a) a united list of most desired features for learning/environment/location/safety-related context awareness systems for SmU and (b) lists of identified systems that cover various components or fragments of learning/environment/ location/safety-related awareness.

4 Towards a Smart University: Developed Components at Bradley University (Examples)

Bradley University (Peoria, IL, U.S.A.) is actively involved in research and development of SmU conceptual models, strategies, smart learning environments, smart classrooms, smart software and hardware systems, etc. in order to move from a traditional university model towards a well-thought and well-discussed smart university model. Several Bradley University pioneering initiatives in the area of design and development of smart classrooms are presented below.

Smart classrooms built (2014–2015, Westlake 316 project). From 2014 to 2016, Bradley University contracted the Crestron company (http://www.crestron.com) to set up top-quality multimedia Web-lecturing and capturing equipment for eleven (11) smart classrooms with different software/hardware configurations and set ups from a generic set of equipment for smart classroom (Fig. 3.2). For example, a smart classroom in room 316A in Westlake Hall of Bradley University is equipped with a) 84” smart board (with smart board projector), (2) HD Pro video camera and corresponding Capture HD software, (3) instructor’s console with a smart control unit, (4) ceiling-mounted projector, (5) ceiling mounted microphones, (6) document camera, (7) speakers., and (8) Ponopto software system for recordings all in-classroom activities, etc.

Fig. 3.2
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A set of smart devices for usual smart classroom

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Smart classroom of the 2nd generation (2017, Bradley 160 project). In 2017, Bradley University and, specifically, the College of Liberal Arts and Sciences (LAS), designed and developed a smart classroom of a new generation [11]—it is considered Phase# 1 (Sep 1, 2016—Feb 1, 2017) of the to-be-developed Center of Smart Education at LAS College and Bradley University in room 160 of Bradley Hall at Bradley University—the so-called Bradley 160 project (Fig. 3.3).

Fig. 3.3
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Smart classroom of 2nd generation at Bradley University–BR160 (with a focus on virtual presence of online/remote students in a classroom and active communication/collaboration of in-classroom instructor and students with remote/online students)

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As of February 1, 2017, it is equipped with (1) a new type of SMART board—SMART Board 84—that actually works as a very big tablet with 84-inch touchable screen (the market cost is about $12,000); (2) twenty one (21) DELL 7459 AIO computers with built-in 3D video cameras and microphones (the market cost is about $1,100 per unit); each computer may serve as both desktop computer as well as flat 24” tablet with touchable screen; (3) ceiling-mounted projectors (market cost is about $1,000), (4) at least three (as of March 2017) 55” big screen TVs (market cost is about $750) for virtual presence in a classroom and communication/ collaboration with remote/online students, (5) multiple video cameras, (6) speakers, (7) three students collaboration areas (big tables with chairs that are close to big screen TVs), and other electronics.

Support of research in Smart University area (Bradley grant REC # 1326809). In 2015, Bradley University OSP awarded one of the co-authors with a grant to support research, design, and develop conceptual models of a smart university, identify suitable software and hardware systems, smart technology, smart pedagogy, etc., in order to identify and investigate multiple aspects of Bradley University transition from a traditional university towards a smart university. A summary of up-to-date research outcomes and findings are already available in various publications by members of research team [11, 22, 23, 37, 38, 39, 40, and 41]. As a result, Bradley University installed a well-recognized national and international profiles in the areas of Smart Education, Smart e-Learning, Smart Classrooms and Smart University.

As an integral part of this research-focused grant, during Phase # 2 of this project (Feb 1–May 15, 2017), the Center for Smart Education will be additionally equipped with multiple identified, analyzed and tested software systems for smart education (as described above) and corresponding smart devices.

Additionally, a special emphasis in this research project is given to installation, analysis and testing of software systems to support students with disabilities in the Center of Smart Education [39, 41].

5 Conclusions. Future Steps

Conclusions. The performed research, and obtained research findings and outcomes enabled us to make the following conclusions:

  1. (1)

    Leading academic intuitions all over the world are investigating ways to transform the traditional university into a smart university and benefit from the advantages of a smart university. Smart University concepts, principles, technologies, systems, and pedagogy will be essential parts of multiple research, design, and development projects in upcoming years.

  2. (2)

    Our vision of SmU is based on the idea that SmU—as a smart system—should implement and demonstrate significant maturity at various “smartness” levels (Table 3.1) or distinctive smart features, including (1) adaptation, (2) sensing (awareness), (3) inferring (logical reasoning), (4) self-learning, (5) anticipation, and (6) self-organization and re-structuring—the corresponding research outcomes are presented in Table 3.2.

  3. (3)

    It is necessary to create a taxonomy of a smart university, i.e. to identify and classify SmU main (a) features, (b) components (smart classrooms, technological resources—systems and technologies, human resources, financial resources, services, etc.), (c) relations (links) between components, (d) interfaces, (e) inputs and outputs, and (f) limits/constraints. The premise will (a) enable SmU designers and developers to identify and predict most effective software, hardware, pedagogy, teaching/learning activities, services, etc., for the next generation of a university—smart university—and (b) help traditional universities to understand, identify, and evaluate paths for a transformation into a smart university. The proposed and developed conceptual modes of SmU are presented in Sect. 3.2 above.

  4. (4)

    Based on our vision of SmU and outcomes of our research, SmU may have multiple components of a traditional university; however, it must have numerous additional components to support and maintain SmU distinctive features—a summary of our research outcomes is presented in Table 3.3 above.

  5. (5)

    One of the most distinctive features of SmU will be multiple software systems that are usually not used by a traditional university. The obtained research data on this topic is summarized in twenty-four (24) tables presented in Sect. 3.3 above. Our research team carefully analyzed 120 + suitable software systems, carefully tested 50+ systems, and recommended 18 open-source (free) and 18 commercial systems for possible deployment by SmU—see Tables 3.7, 3.11, 3.15, 3.19, 3.23, 3.27 for details.

  6. (6)

    Bradley University already created and implemented several smart classrooms in its curricula. A design and development of a pioneering smart classroom of the 2nd generation started in 2016. The details of developed smart classrooms are described in Sect. 3.4 above. Based on the pilot teaching of classes in smart classrooms, the obtained feedback from faculty and students clearly shows a keen interest from students in high-tech smart education, a significant research interest from faculty to implement various smart systems and devices into smart classroom and smart education, and, in general, proved the correctness of major design and development proposals and solution to build and actively use smart classroom in Bradley curriculum.

Next steps. The next steps (Summer 2017—December 2018) of this multi-aspect research, design, and development project deal with

  1. (1)

    Implementation, analysis, testing, and quality assessment of numerous components of smart software and hardware systems, smart devices, smart technology, and smart pedagogy in everyday teaching of classes in smart classrooms.

  2. (2)

    Implementation, analysis, testing, and quality assessment of numerous components of smart software and hardware systems, smart devices, and smart technology at Bradley Hall (the home of majority of departments of the College of Liberal Arts and Sciences) and in some areas of the Bradley University campus.

  3. (3)

    Organization and implementation of summative and formative evaluations of local and remote students and learners, faculty and professional staff, administrators, and university visitors with a focus to collect sufficient data on quality of SmU main components—features, software, technologies, hardware, services, etc.

  4. (4)

    Creation of a clear set of recommendations (technological, structural, financial, curricula, etc.) regarding a transition of a traditional university into a smart university.