**2.2 The MOOC-as-course augmentation for faculty and as resource for PLErify teaching learning**

In AI age, faculty must face their new roles as programmer and owner/builder of learning environments of their courses that they must update per semester. Professors who remain indifferent in the new reality of a virtualized higher education vis-a-vis their expanded roles and new responsibilities will face major challenges as industry-driven automation-driven AI persistently seek dormant or stagnant unchanging areas to automate and simplify. A faculty [6] from Scotland recalls his very productive sabbatical spent at Google (*Big Tech and AI-driven*) in Silicon Valley. In that sabbatical, this academically trained faculty learned and eventually re-adapted his purely academic mindset (coding) to meld with that of a practitioner's mindset and started building coding projects that work in real life. Faculty (*particularly those in the sciences and engineering*) can follow Barker's example and come out technologically empowered fusing the academic with the practical real world and impart the same mentality to its students, that is, college to career.

Regardless, MOOC courses will continue to be made available online to anybody for free, or at a minimal cost. Boosting acceleration of acceptance by universities globally, MOOC continues an upward evolution toward a better practical higher education option for both career (*skills training or mastery certifications system*) and advanced degrees (*bachelors, masters, and doctorate*)*.* Also, with student advancement (*and their interest in mind*) and ease of teaching for instructors as prime motivators for MOOC development, there is truly so much about the MOOC system to be appreciated that will make higher education leaner, more efficient, very current, and very affordable.

Another very encouragingly useful aspect of MOOC that is only now being realized is, they add to the personalization of learning both as a teaching resource for instructors and as an inexpensive way for students to obtain advanced degrees and lastly but more importantly to upgrade skills of work professionals. MOOC business model is being revamped and, evolving toward a more profitable version, thereby offering fee-based enrollments where certification of completion is a student's objective. The free aspect of the MOOC model however can be used by all faculty as another teaching tool. For example, professors can require students to take the MOOC version of their course offered by other universities (*now estimated at 900*) shown in **Figure 1**, before students take the real course. In a PLErify state, courses already in MOOC database can be treated as a required mastery before registering and enrolling in the equivalent actual university traditional course or program unloading faculty of heavy teaching. Some tedious portions of the course can be bypassed having mastered it beforehand through MOOC.

While debates and experimentation continue to grow in artificial intelligence, PLErify App (2007) remains a precursor to the above scenarios. Even though the core of educational technology research centers on academic applications, academe, ironically remains the most resistant and the slowest to adapt to a scenario of AI, Big Data and IoT whichwhen taken as a group suddenly changes the course delivery game. Groups in the tech industry persistently hint at a future without a human teacher and professor, as computer scientists now and then flirt with the idea of adding consciousness to a computer. At this time though, a robot cannot actually augment human cognitive and emotional capabilities through what they claim as smarter machines currently experimented in other industries (automobile industry). I would simply and safely assume that use of virtual robot assistant is an easy spillover for use in higher education [2].

#### *New Innovations in Engineering Education and Naval Engineering*

#### **Figure 1.**

*The hard-to-ignore breadth and reach of MOOC globally.*

It is best to speculate that whatever happens in the corporate industry will, in some form happen in the education industry. The digital society interconnects everything, from machines and app to the software/hardware; from knowledgebase to users; from different variety and degrees of transactional computing; from the teachers to the students; from the businesses to the consumers; from the students to the universities; from the faculty to the students to the universities; and finally, from the ordinary users to everything which can occur via our desktops and our handhelds. Apocalyptic ideas have been flouted at global corporate e-learning events that hint at the idea of massification to replace traditional creative teaching without a human teacher, which may appeal to select academicians who fall into the trappings of "easy teaching," that is, less classroom presence and letting the students watch video lectures and digitized .pdf files of the syllabus. Given that these handheld tools are now a normal part of everyday life blending the here, the now, and the future, a DIY culture for course building becomes inevitable. Embodied by the PLErify application (2007), the DIY mindset provides a solid training ground for ubiquitous computing vis-a-vis course building as it involves an interplay of a variety of cognitive skills combined with digital conversion of ideas into a viewable medium.

Today, 24/7 we carry our smartphones, iPad, and other handhelds also known as mini/microcomputers, more powerful than any computers built in the 1980s and the 1990s, with us and with these technologies we socialize, network, listen to music, share photos, financially transact, chat on live video, and much more, thereby doing tasks never before possible at the very same period of time educators were theorizing on learner styles, cognitive styles, etc. My own observation over this past decade is that while educators spent so much time researching learner styles and cognitive styles, they believed impacted learning, Big Tech simply went ahead and produced a plethora of handhelds and smartphones that rapidly jumpstarted user acquiring tech skills in turn accelerating mastery that are, fortunately, usable in both daily life and university learning but unfortunately left out those who could not keep up with the constant roll-out of new versions and models. What that phase did to each of us was it made us tech-savvy and I would argue, smarter. Now, certain tech user interactions have become ingrained for majority of us smartphone and multiple device owner and users. Majority of learner tasks to: make choices, complete learner tasks, solve problems, think about thinking (metacognition), compute, analyze have become second nature.

Indeed, technology has a very democratizing effect on its dedicated users from acquiring uniformity of skills to performing actions to obtain something back as a result; skills, which by the way, are also transferable to other domains from

**53**

**Figure 2.**

*Technology infrastructure to teach.*

*Personalizing Course Design, Build and Delivery Using PLErify*

personal, to business, to higher education with specific attention to learners. All users get it. We can turn on the device, charge the device, download and use apps, transact, collaborate, blog, share documents, and so many other things that it is now second nature to have (*as opposed to not have*) our smart devices even while we sleep. Technology has intercepted our lives in unimaginable and remarkable ways psychologically but best of all, educationally. I must conclude that though technology tools are not advisable for use by children, technology for mature adults is an

The timely re-entry of computational [7] tools to teach creatively befits this era of our technology-driven education. Less intervention on how students create their learning paths as they meld new learning with what they already know in working memory gives students a better grasp at how to manage their interactions and the accumulation of those interactions in a self-directed way exemplified by the constructivist didactic model used in the Virtual Mentor Project notably learning by

The actors on stage in the world of tech-based teaching and learning and their functions in the teaching learning equation are summarized with one infrastructure

*Software applications* accessible on the web allow both instructors (*course makers*)

and students (*users*) to manipulate course content to create, present, and store. *Learning Management Systems* (*LMS*) are prepackaged applications that act as an administrative tool to manage the online course, the students who enroll, and the professor who offers the courses. *Artificial intelligence* (AI) is the byproduct of deep learning, huge swathes of databases within a database that when meshed together gives it intelligence though within a limit, that is, you can program a robot to do certain things that will be limited to the amount of intelligence you put in it. A human is still in command and an ill-programmed robot like a biased robot gives

*DOI: http://dx.doi.org/10.5772/intechopen.85414*

additive rather than a subtractive experience.

in common: connection to the Internet (**Figure 2**).

asking LBA Project [8].

**3. Didactic models for creative computational teaching**

*Personalizing Course Design, Build and Delivery Using PLErify DOI: http://dx.doi.org/10.5772/intechopen.85414*

*New Innovations in Engineering Education and Naval Engineering*

*The hard-to-ignore breadth and reach of MOOC globally.*

It is best to speculate that whatever happens in the corporate industry will, in some form happen in the education industry. The digital society interconnects everything, from machines and app to the software/hardware; from knowledgebase to users; from different variety and degrees of transactional computing; from the teachers to the students; from the businesses to the consumers; from the students to the universities; from the faculty to the students to the universities; and finally, from the ordinary users to everything which can occur via our desktops and our handhelds. Apocalyptic ideas have been flouted at global corporate e-learning events that hint at the idea of massification to replace traditional creative teaching without a human teacher, which may appeal to select academicians who fall into the trappings of "easy teaching," that is, less classroom presence and letting the students watch video lectures and digitized .pdf files of the syllabus. Given that these handheld tools are now a normal part of everyday life blending the here, the now, and the future, a DIY culture for course building becomes inevitable. Embodied by the PLErify application (2007), the DIY mindset provides a solid training ground for ubiquitous computing vis-a-vis course building as it involves an interplay of a variety of cognitive skills combined with digital conversion of ideas into a viewable medium.

Today, 24/7 we carry our smartphones, iPad, and other handhelds also known as mini/microcomputers, more powerful than any computers built in the 1980s and the 1990s, with us and with these technologies we socialize, network, listen to music, share photos, financially transact, chat on live video, and much more, thereby doing tasks never before possible at the very same period of time educators were theorizing on learner styles, cognitive styles, etc. My own observation over this past decade is that while educators spent so much time researching learner styles and cognitive styles, they believed impacted learning, Big Tech simply went ahead and produced a plethora of handhelds and smartphones that rapidly jumpstarted user acquiring tech skills in turn accelerating mastery that are, fortunately, usable in both daily life and university learning but unfortunately left out those who could not keep up with the constant roll-out of new versions and models. What that phase did to each of us was it made us tech-savvy and I would argue, smarter. Now, certain tech user interactions have become ingrained for majority of us smartphone and multiple device owner and users. Majority of learner tasks to: make choices, complete learner tasks, solve problems, think about thinking (metacognition),

Indeed, technology has a very democratizing effect on its dedicated users from

acquiring uniformity of skills to performing actions to obtain something back as a result; skills, which by the way, are also transferable to other domains from

**52**

**Figure 1.**

compute, analyze have become second nature.

personal, to business, to higher education with specific attention to learners. All users get it. We can turn on the device, charge the device, download and use apps, transact, collaborate, blog, share documents, and so many other things that it is now second nature to have (*as opposed to not have*) our smart devices even while we sleep. Technology has intercepted our lives in unimaginable and remarkable ways psychologically but best of all, educationally. I must conclude that though technology tools are not advisable for use by children, technology for mature adults is an additive rather than a subtractive experience.
