Preamble
Adaptiva Corp (the owner of Coursewell.com) is looking for investors and partners to automate, scale up and accelerate Coursewell operations and marketing by developing and leveraging AI/Machine Learning technologies.
Executive Summary
With private and public grants and sponsorships, from SMP, SGMI, NSF, DoD, MyCAA, MedCerts, etc., Coursewell.com has provided no-cost, personalized, portable, high-demand career certification training programs to job-seekers (for instance, military spouses while their partners are on active duty.) Now, Coursewell seeks to scale up its operations to serve global job-seekers and employers. Coursewell creates on-the-job training opportunities by matching employers’ and partners’ needs with job-seekers wants.
To deliver its online courses and consistently support participants/students, Coursewell continues to develop and deploy a new AI-based, Learning Management System (ai-LMS) as well as an adaptive learning video-content training app using an AI-enabled SaaS cloud platform. The new system and app will replace the current time-consuming manual operations (i.e., registration, fee collection, content creation, content delivery, assessments, constant feedback, and so on).
To minimize the impact of the AI transformational process (which will take 6- to 24 months) and to reduce capital outlays; initially, routine operations will be outsourced to external advisers/mentors/experts/marketers under the supervision of the program director (Prof. Walter Rodriguez, PhD, PE) ---who obtained the initial multi-year, multi-million-dollar grant-funding (i.e., financial assistance) from the government (DoD) and private industry partners.
Coursewell is seeking to quickly scale operations and marketing efforts.
Coursewell AI Strategic-Implementation Plan for (1) attaining Coursewell’s cost-leadership/focused-personalization strategy; and (2) quickly expanding operations and offerings with minimal human intervention, will consist of seeking to automate all processes and leverage Generative and Interactive AI technologies—including ML, NLP, robots, by extrapolating or inferencing from Porter’s, Kotter's and Ng’s trans-formational frameworks. Advisers/mentors will continue to use their core competencies (i.e., designing individualized programs and supporting at-risk participants) while being liberated from routine administrative and clerical tasks. By developing and implementing AI (machine-human) symbiotic collaboration and technologies, Coursewell will be able to save both time and money as well as add- and create value for all its stakeholders (for instance, liberating advisers/mentors from routine tasks).
Coursewell will become a smart enterprise by attaining the flexibility of a small/nimble organization---while seeking the economies of scale of a large organization, as recalled from strategy thinkers (i.e., Applegate, Porter).
The following developments and processes will provide “economies of scale” and quick scalability as well as efficiencies and productivity gains with fewer workers: (a) 24-7 Smart Receptionist/Sentry; (b) Robo-RA/TA; (c) Telepresence Customer Support; (d) Smartly-trained Customer-Service AI/Robot; and (e) AI-LMS and adaptive content delivery as well as participant success-tracking, in support of Coursewell low-tuition and focused adaptive/individualization/personalization strategy.
Justification: While Coursewell currently has a relatively high completion rate (87.6%), it has been due to the persistent and consistently high level of online support provided (via the Internet, chats, e-mail, VoIP, video, and other telecommunication tools) to all participants (i.e., military spouses). However, this is a very labor-intensive process that might be aided by a smart partnership between advisors/mentors and AI tools and strategies.
““In times of disruption, artificial intelligence, particularly the ubiquitous machine learning, is being rapidly integrated into online working environments in academia and industry. Primarily, these transformative technologies can help automate and perform continuous routine tasks using speed, efficiency, and effectiveness to gather and analyze massive amounts of data and information. This research illustrates ways in which machine learning can benefit learners and organizations—-by making learners and workers work smarter and, more importantly, improve their ubiquitous learning environment anytime, anyplace. Humans can learn while working and studying by integrating both reinforcement learning and supervised learning paradigms, and by augmenting, supplementing or complementing with workers’ humanness, unique skills, creativity, emotions, passions, and tacit knowledge. Furthermore, machine learning can track the humans learning process by learning from its experience—observing and analyzing the knowledge acquisition process, progress, and difficulties. And machine learning algorithms and agents can suggest new learning paths and approaches. In addition to exploring how machine learning can enhance human learning, this paper investigates how it can assist learning without impinging on natural human and social learning development—rather than substituting or supplementing the recall. And integrating and enhancing work performance by minimizing rather than supplanting tedious tasks with automation and artificial intelligence.” Rodriguez, Walter, Angle, Patricia, and Snyder, Michelle (2020). Upcoming Paper: “How Machine Learning Can Enhance Human Learning in Times of Disruption.” To be submitted to Ubiquitous Learning: An International Journal.”
Current State
Coursewell.com currently provides, no-cost to low-cost, personalized career certification training programs to world-wide job-seekers (mainly military spouses---while their partners are on active duty.) To design, deliver, and support these online courses world-wide, Coursewell developed and deployed both a mobile app and a Learning Management System. These app and system reside on the Cloud (Amazon Web Services) servers. And the online courses are accessible 24-7 from the participants’ mobile devices via cloud computing technologies and a video-trainer, ubiquitously--- anytime, anywhere. To assist with the online course delivery, Coursewell currently uses Canvas LMS, e-mail and telecommunications to coordinate all activities—including recruiting, program design, assessments, and advising. For instance, it uses e-mail to: (1) coordinate with third-party providers—including specialized marketeers that identify prospective participants; and (2) coordinate with the various third-party video training providers. Further, it uses the LMS to create and post course-content and interactive learning activities. Coursewell’s mentors/advisors assess all prospective participants and prepares an individualized plan-of-study for each participant seeking a job in the healthcare or technology industries. Coursewell is currently hindered by low-productivity and inefficient communication strategies. And it’s seeking partners and venture capital to develop and deploy artificial intelligence tools & strategies, in order to assist in the assessment and automated preparation of the participants’ plan-of-studies as well as supporting participants 24-7 (with minimal human intervention.) As a no-cost or low-cost provider of individualized online career certification programs, Coursewell focuses its core competencies (i.e., personalizing a career-path based on the participants’ background and the future employer needs via on-the-job training opportunities.) Coursewell have been pursuing both “cost-leadership” and “focused-individualization” strategies that could be aided by AI: that is, low-cost courses and focus on mass individualization/personalization of programs. Currently, Coursewell is seeking to use AI technologies to improve process efficiency and productivity. This seems to be fully consistent with a dual cost leadership-focus strategy, since a partnership between advisors/mentors and AI can make this possible. Of course, Coursewell will still choose to emphasize cost-leadership, while using AI-human-computer assisted tools for generating both personalized programs and predictive analytics. The implementation will fit Coursewell’s hybrid strategy, by leveraging both (a) innovative AI technologies to augment operations; and (b) experienced advisors/mentors. By freeing the advisors/mentors from all the daily tasks, the hybrid strategy will bring new added-value to Coursewell stakeholders. AI predictive tools and strategies will assist Coursewell in improving participants’ persistence and completion rates in the program (Table 1), given that a significant number of participants tend to drop from the program (or do not take the certification exam) without constant adviser/mentor intervention (see “Improving Persistence …” paper on LinkedIn).
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Table 1 – Participants: Completion Rate
Total Participants in the Training: 3343
Completion Rate: 87.6%
Certification Pass Rate 70.9%
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Proposed AI initiative for Coursewell Coursewell.com is proposing an innovative multi-faceted AI initiative to benefit from using AI MC, NLP and robotics--by combining humans (advisers/mentors) with autonomous robotic functionality (i.e., more than one function) on the following organizational-processes: (1) 24-7 Receptionist/Sentry: A welcoming (anthropomorphic) robot at the reception desk to both “screen” and “safely” protect and direct visitors to the correct individual [Note: Needed in times of mass school shootings, and a world-wide pandemic]; (2) Just-in Time Lunch Delivery: Take orders and bring warm meals to employees’ desk--exactly when they are going to be hungry based on MC-learnt and sensing employees habits and patterns: (3) On-demand self-driven car-robot: Based on known employees’ schedule/calendar, alert, pick-up and drive employees to the airport or other destinations as needed (per online calendar); (4) AI-Robo-RA/TA: A personal AI research assistant/teaching assistant to help with the on-site computer summer labs communications and preparations; (5) AI-LMS and adaptive content delivery. And, finally: (6) AI-Telepresence-Customer Support: A well-trained Customer-Service (CRM)/Marketing AI/robot will accompany Coursewell’s salesforce or advisers and perform routine administrative, communications and marketing tasks while on the route and upon arrival at the site (i.e., military base). Pursuing Coursewell’s vision and core competencies (i.e., design and deliver on-demand (24-7) personalized career certification training to anyone/any place at the lowest possible cost), we will deploy multi-purpose AI robots to support both the focus (personalization) and cost leadership hybrid strategy. Coursewell will be able to save both time and money as well as add value and convenience to all its stakeholders (i.e., free them from routine tasks). The processes described above will provide “economies of scale” as well as quickly “scalable” efficiencies and effectiveness. This will be an improvement beyond our current telepresence robot environment (i.e., the telepresence “anybots”.) The hired Chief AI Officer (CAIO) will have the additional role and duties of collecting and assuring the “underlying (AI) requirement (e.g., data availability)” as well as the data required to train the AI/ML/NLP-powered robots. Of course, the CEO/Chief Innovator Officer (Dr. Rodriguez) will ensure that Coursewell will have access to a sustainable funding source while developing the integrated AI/CRM/ERP information systems. Pursuant to Coursewell well-fitted robotic initiatives on both business strategy and IT strategy, the “increasing persistence/retention” goal will be supported by the CEO/Chief Innovation Officer, i.e., “ped KPIs (e.g., achieving a 10% decrease in students dropping a particular course”). Regarding the technical considerations, it would be necessary to have reliable information systems (i.e., databases etc.) as well as a robust IT/AI infrastructure (i.e., networks) sustaining/supporting, mobile and cloud computing technologies from AWS or Microsoft or other cloud vendors. Further, we would need to identify training examples. Once identified, the remaining ‘learning’ process is essentially (I think) a computational problem that would not necessarily directly involve more people. Of course, having access to faster machines/processors (newest Amazon’s MC chips?) that can effectively ‘learn’ faster will be advantageous. Further given that servers will run data analytics and other intensive processes, the 24- 7 data center will have to be very robust and reliable. Finally, in evaluating the hardware platform vs Infrastructure as a Service (IaaS), we would need to consider: (a) the need for specialized inferencing hardware; (b) determine the “floating-point” performance (the real, rather than peak) when the system calculations are governed by memory and cache bandwidth performance; (c) analyze many-core or massive parallelism needed to train Coursewell’s large data sets; and (d) research reduced-precision data types (i.e., niche optimization.) Coursewell has identified and will develop the following AI NLP/NLG hybrid cost-leadership and focus (mass personalization) strategies:
a. NLP Sentiment Analysis: By implementing “sentiment analysis” algorithms and apps, Coursewell will be able to automate the extraction of meaning (or making sense) from hundreds of emails and voice-mail messages received, on a daily basis, asking about the DoD MyCAA scholarship. Although the “emotion” in the communications are not explicitly stated (but somewhat implicit), an extraction via sentiment analysis might serve as a competitive edge, since our competitors in the career certification training business are fairly behind in the application of AI NLP.
b. NLP Information Extraction: By automatically extracting and structuring data from unstructured text messages or pixeled images, Coursewell will be able to “extract” data (i.e. entity extraction), such as names, addresses, course fees, locations, etc. In addition, could use “fact extraction” to supply Coursewell participants’ spreadsheets and databases with the structured data and information. By automating this process, Coursewell will pass-on the cost-saving of automation in support of cost-leadership as well as feed social media marketing initiatives.
c. NLP Semantic Search: Semantic (smart) searches will allow the Coursewell site to address complex questions automatically, rather than wait for an advisor/mentor.
d. NLP Automated Reply to Questions (or QA): Implementation of chatbots will also save time and money for all stakeholders, in support of our cost-leadership and focus strategies—particularly, mass personalization. In addition, NLP powered customer support chatbots, will permit understanding of the participants’ questions and logically reply to the message originator (i.e., potential trainees). Further, it will streamline basic administrative operations, such as, financial aid processing, invoice processing and so on.
e. NLP to Keep Advisors/Mentors Interested: Rather than spending lots of time in routine or monotonous tasks, advisors/mentors will be more efficient, effective, productive, and creative. So, it might help improve performance and moral as well—by freeing advisors/mentors to address personal issues presented by at risk participants. In this way, Coursewell will be able to reduce the cost of the training, while being able to mass customize, adapt and personalize career training certification programs.
Coursewell: Plan of Action and Criteria for Success
Objective: Coursewell AI initiative will automate most current business communication and processes by developing and implementing AI ML/NLP/Robotics coupled with aiLMS/CRM/ERP/BPE systems. [“From predicting drop-out rates of participants to personalizing product offers to predictively improving product performance to supporting customer segmentation and target marketing to visualizing data for pragmatic decision-making … to implement smarter, automated processes that can liberate staff time for increased focus on core operations and user experience.”]
Key Results/Key Performance Indicator: Ultimately, as an MIT advisor indicated: we should “… peg KPIs (e.g., achieving a 10% decrease in students dropping a particular course).” And pursuant to Google’s OKR framework. The Coursewell founder with the assistance of a Chief AI Officer (to be hired) will lead the implementation of the proposed AI initiative. While the founder will set the overall business strategy and seek funding, the CAIO will hire IT/AI staff or outsource the development of the integrated AI applications and vendors. [Of course, funding permitting, we will start to develop our in-house AI team, as suggested by Andrew Ng in his AI Strategy writings.] The technical considerations and requirements for deploying and implementing Coursewell AI will involve developing/refining an IT/AI Strategic plan, following Kotter's and Ng’s recommendations, as well as a clear connection between Coursewell business-value for all stakeholders and the AI technologies to be implemented. This will be governed by the current in-house technical limitations and our ability to attract investors and AI developers.
The key factors will be: (a) assess the outcomes that would benefit the most from AI; (b) analyze the most suitable AI technologies available from vendors; (c) match outcomes with the technologies; and (d) plan for key use cases and best implementation practices. Of course, as suggested by Brian Charles, “underlying requirement (e.g., data availability) in considering the tech requirements … and beginning to peg KPIs (e.g., achieving a 10% decrease in students dropping a particular course) might be useful for you to begin considering. Methodology: Using a modified SDLC (System Development Life-Cycle) model, the technical development and implementation process may be conceptualized as: [Define AI strategy] > [Prepare Data & Evaluate (concomitantly with AI Business Case Selection] > [Assess AI Vendors (concomitantly with Performance)] > [Develop AI Pilot and Experimentation] > [Production/Implementation (concomitantly with Evaluation)] > [Cycle back to Re-defining the AI strategy.] To have the best chance of success (and avoid pitfalls), Coursewell AI Plan-ofAction will follow Kotter's (1996) and Ng’s (2018) recommended transformational stages, as well as the insights gained from the MIT AI Strategy course. And will evaluate staff results using Google Objectives and Key Results (OKR) framework.
Below are the actions needed for leading the Coursewell AI transformational change:
I. Using Porter 5 Forces Framework, I will re-examine the Career Certification Training market to discover untapped opportunities and avoid surprises. And I reevaluate and reconfirm the generic cost leadership/focused personalized strategies with stakeholders.
II. I will hire a Chief AI Officer (CAIO) to lead the AI development efforts and research the companies and partners that might be able to assist us in leading the transformational efforts. In addition, s/he will propose a fasttrack schedule (time-line) for completion of an AI Pilot that can be completed in 6- to 24-month using state-of-the-art project management software.
III. Since students/participants’ data is a Critical Success Factor (CSF)-asset for Coursewell, we will develop an AI Strategy specific to the career certification training industry. And to create value Coursewell will establish an amalgamated data warehouse to share data and glean information across the organization as well as distinguish truly valuable data from non-valuable or low-value data. IV. As proof-of-concept, The CAIO will conduct the first AI Pilot project in a feasible area where Coursewell has the most opportunities to gain, for instance, “sentiment analysis” algorithms and apps, Coursewell will be able to automate the extraction of meaning (or making sense) from hundreds of emails and voice-mail messages received, on a daily basis, asking about the DoD MyCAA scholarship. Further, as Brian Charles indicated “… deploying NLP for conducting sentiment analysis …” will be our #1 pursuit: “in information extraction, in semantic search for addressing website queries, in QA and in maintaining the interest levels of advisors/mentors by alleviating their rote work.”
V. In a concurrent, second pilot project Coursewell will develop an AI-based Learning Management System (ai-LMS) as well as an adaptive learning video-content training system using Cloud services and mobile apps by improving upon its current systems.
VI. I will refine Coursewell's vision, in order to align organizational support structures with our core competencies (i.e., designing and delivering personalized programs.)
VII. I will clearly communicate Coursewell vision (i.e., automating all processes, in order to attain the cost-leadership and focused personalization strategies) to all stakeholders as well as the need for spending the current capital and resources on AI automation.
VIII. I will remove the current outdated (non-automated) online registration and video training systems that are hindering the successful implementation of the AI low-cost/personalization strategy. IX. In coordination with the CAIO, the CEO will help re-engineer the performance improvements, so that we can implement the AI/advisers/mentors symbiotic and synergistic collaboration as quickly, productively, efficiently and effectively as possible.
X. As CEO/Chief Innovation Officer, in coordination with all stakeholders, Dr. Rodriguez will develop and implement the policies needed to grantee that AI systems will be properly supervised by humans to prevent ethical/privacy/security issues. And I will hire and re-train employees, so they will lead the advising/mentoring processes, based on their experience helping participants/students.
XI. The CAIO, will recruit and build an in-house AI team and institutionalized AI training. This training will be conducted by the CAIO in coordination with the CEO and outside consultants. Over 8-hours per week, will be allocated for training, since the AI field is advancing very quickly.
XII. A recruiting/talent company will be used to continuously seek smart, ethical, sensitive and talented individuals that have a proven record of working both with people and machines. And assess and measure staff’s project accomplishments using Google’s OKRs.
XIII. Finally, in the initial pilot projects, Coursewell will seek to continue building technological assets that are difficult to emulate but are closely aligned with Coursewell strategy in its niche market (career certification training).