The Bachelor of Science in Technological Entrepreneurship and Management program consists of a 120-credit by completing:

• Entrepreneurship & Innovation: 18 Credits
• Business & Management: 15 credits
• Technology & Programming: 30 credits
• Quantitative and Analytical: 9 credits
• Entrepreneurship Capstone Project or Venture Lab Capstone Project: 3 credits
• General Studies: 30 credits
• Concentration: 15 credits

All the students must complete an 8 months of profession internship or industry experience as a part of graduation requirements.

Student work includes direct or indirect faculty instruction. Academic engagement may include, but is not limited to, submitting an academic assignment, viewing class lectures on campus or online (synchronous or asynchronous), taking an examination, completing an interactive tutorial or computer-assisted instruction, attending a study group that is assigned by the institution, contributing to an academic online discussion, initiating contact with a faculty member to ask a question about the academic subject studied in the course, conducting laboratory work, and completing an externship or internship. Preparation is typically homework, such as reading and study time, and completing assignments and projects. Therefore, a three (3) semester credit hour course requires 135 semester hours (45) hours of academic engagement and 90 hours of preparation).

Detailed Description of Each Grading Criteria:

Westcliff University makes use of Grading Rubrics for scoring grades in many assignments. Grading or scoring rubrics are used as a tool used to delineate criteria and expectations pertaining to assignments and to establish an objective consistency in grading. Typically, rubrics are divided into components so as to allow for a more direct and precise measurement and interpretation of assignments. Hence, rubrics are designed to provide guidelines for grading assignments and represent a systematic appraisal of student-work only from this perspective. The final grading of all assignments will have a subjective component that typically includes the instructor’s interpretations, judgments, and any policies pertaining to assignments.

A. Grading Criteria for Class Participation

For students participating in a Hybrid course, students will receive two weekly Participation grades:

(1) Onsite Class Session (OCS) Discussion:
Students are expected to attend their Onsite Class Session each week. Preparation for class involves reading the materials and working through, in some detail, the case preparation for class in advance. By preparing these questions, students will get the most learning out of the class. While in class, more participation will lead to increases in the quality and rigor not only of the class but of other student’s learning modalities as well. Westcliff University provides an open forum environment. There is no limit on the discussion in which you may involve yourself.
AND –
(2) Online Discussion Board Discussions
Each week, students will be assigned 1-3 Discussion Questions. For each Discussion Question, students must post an initial answer in the Discussion Board on their course Global Academic Portal (GAP) by the assigned deadline each week as identified in the syllabus. Students must then post a Peer Response for each Discussion Question by the deadline that same week as identified in the syllabus. The GAP can be accessed online at gap.westcliff.edu.
Students are expected to answer each discussion question critically by using your textbook, library-based research, and the Internet, and actively participate in class.

All discussion responses should be at least one (1) paragraph in length (200 words approximately) with significant, rigorous content. Your response should reflect your ability to conduct research and include citations. You should also present your analysis and support it with specific examples.

Responses to other learners’ analyses should add substance, request clarification, provide a different perspective, or challenge the assertions made by providing real or hypothetical scenarios that the original analysis does not adequately address. It is expected that your peer response will be at least one (1) paragraph in length (100 words approximately). It is also good practice to provide normal, supportive comments. Everyone appreciates this feedback. Remember, the purpose of course discussions are to stimulate academic debate.

In assigning grades to class discussion, faculty will focus primarily on the quality of your input; however, it usually takes at least some quantity of written content for us to make that evaluation.

Good case discussions take the group further than any one individual or study group can go on their own. However, it takes at least a certain quantity of participation to make that evaluation. Instructors will develop grades and scores based on the quality and quantity of your contributions.

At the undergraduate-level, discussion questions can be based on any one (or combination) of the following resources:

• Textbook, current and previous chapter(s)
• Other readings
• Research (journals, periodicals, and other electronic resources)
• Lecture

The University makes a concerted effort to promote a variety of discussion questions that are related to the current course and/or its content as it relates to the field in business in general.

In general, the instructors’ criteria are:

1. Are points made relevant to the discussion?
2. Do they go beyond a mere recitation of case facts, and are implications clearly drawn?
3. Is there evidence of analysis rather than expression of opinion?
4. Are comments linked to those of others?
5. Did the contribution further the class’s understanding of issues?

Students who neglect to submit their Class Participation responses (either answer to discussion questions or responses to classmates/faculty) by the stated weekly deadlines will be deducted up to 15% of the online participation points possible for that week. Discussion Boards close on Sunday of each week at 11:59 p.m. at which time students are no longer able to post responses and receive no credit for missed posts. Technological issues are not considered valid grounds for late assignment submission. Students are responsible for printing their own assignments, when necessary. Unless an Incomplete grade has been granted, assignments submitted after the last day of class will not be accepted.

B. Grading Criteria for Professional Assignments:

Quantitative Courses (Math, Statistics, Finance, Economics, etc.):
In Weeks 2 and 6, students will generally write a 2-3-page paper in response to a case study or similar assignment provided by your professor (assignment length and content can vary). Student answers are to be clear, well-organized, and specific. Provide a concise, cogent argument and include details to support your response.

Non-Quantitative Courses
In Weeks 3 and 6 (if applicable), students will generally write a 2-3-page paper in response to a case study or similar assignment provided by your professor (assignment length and content can vary). Student answers are to be clear, well-organized, and specific. Provide a concise, cogent argument and include details to support your response.

C. Projects and Capstone

Some classes will have a team project in lieu of an examination. While each course will have different project templates, the deliverables will all be the same:

• a. Team Project Contract & Deliverable document due at the end of week 2;
• b. Draft report due (for content feedback only from faculty) at the end of week 6.
• c. Team project submission and presentation during week 8 class session.

The Capstone course culminates the learning experience by requiring students to apply their knowledge and skills in a comprehensive team project. This follows a structured timeline: teams submit a Project Contract and Deliverable plan by the end of week 2, provide a draft report by week 6 for faculty feedback, and finalize their project with a formal submission and presentation during the week 8 class session. The capstone fosters collaboration, critical thinking, and real-world problem-solving, allowing students to demonstrate their mastery of course concepts through practical application.

D. Grading Criteria for Comprehensive Learning Assessments (CLAs):

CLAs are comprehensive assignments that provide evidence of how well students have mastered the course content and test the students on all the Course Learning Outcomes. CLAs measure student achievement of CLOs in a way that goes beyond rote memorization and gauges true understanding and mastery of course content. CLAs can include assignments such as case study analyses, research papers, and/or student presentations. The answers provided to undergraduate level CLA’s must demonstrate a broad view of organizational performance factors from the general management perspective that demonstrate concepts pertaining to effective leadership and management in the 21st century globalized business economy. One of the grading criteria requirements is that answers provided exhibit skills that promote and integrate program learning outcomes and should include decision-making, strategic management, creativity and innovation, leadership, problem-solving and real-time business application. Answers must also demonstrate the student’s ability to research and demonstrate an undergraduate writing level.

a. Comprehensive Learning Assessment (CLA 1)
In Week 5 (or 4 for quantitative courses), students are to write a 4-6-page minimum, APA-formatted paper in response to a case study or similar assignment provided by the professor. Students must reference the number of peer-reviewed sources beyond the course materials, as identified in the course syllabus. Students’ answers are to be clear, well-organized, and specific. Provide a concise, cogent argument, and include details to support your response. CLA 1 focuses on assessing course foundations and the student’s ability to define and understand its main concepts.

b. Comprehensive Learning Assessment (CLA 2)
In Week 7 students complete their CLA2, which is the logical culmination of the course. Your CLA2 submission (cumulative report) should be a minimum of 4-6 pages in length. The CLA assignments encompass the learning outcomes for this course and are designed to demonstrate what has been learning or achieved by the student. CLA 2 measures the student’s competency and mastery of the course concepts, particularly the application of those concepts.

Assessment for courses requiring Lab work
A core courses will require completion of lab work instead of discussion forum posts. The lab portion of the course will be monitored throughout the eight-week session, where students will have to complete a lab milestone each week. The objective of subsequent lab will be decided on the basis of the output of preceding lab, so skipping lab work any week will be possible. Only students who complete the milestone of the eight weeks will get 15% credit for their lab work. The other 85% credit will be similar to the assessment for courses not requiring Lab work.

The minimum academic requirements to apply to the Bachelor of Science Program in Technological Entrepreneurship and Management:

An applicant must have completed a high school diploma or its equivalent (A- Level – 3.5 Credits; GED – 550 Points) from a regionally or nationally accredited institution to be eligible to apply for entrance into Westcliff University. High school diploma degrees obtained outside of the United States will only be accepted if they have been evaluated by a member in good standing of the National Association of Credential Evaluation Services (NACES) or another nationally recognized credentialing body. In this case, the listed U.S. degree equivalency will be used. A minimum of 2.0 cumulative GPA is required.

English Language Proficiency Assessment

Prospective students whose native language is not English and who have not earned a degree from an appropriately accredited institution where English is the primary language of instruction must demonstrate college-level proficiency in English through one of the following methods for admission:

• A minimum score of 500 on the paper-based Test of English as a Foreign Language (TOEFL PBT), or 61 on the Internet-Based Test (iBT), a 6.0 on the International English Language Test (IELTS), or 44 on the Pearson Test of English Academic Score Report.
• A high school completed at an accredited/recognized high school (where the medium of instruction is English).

Technology Entrepreneurship: This course provides a comprehensive introduction to the principles and practices of technology entrepreneurship. It examines how technology-based ventures are created, developed, and managed. Students will learn to identify entrepreneurial opportunities, develop innovative business models, and implement commercialization strategies to successfully launch and sustain technology startups.

Emerging Technologies for Entrepreneurs: This course introduces students to contemporary and disruptive technologies shaping the entrepreneurial landscape. It covers key emerging technologies such as artificial intelligence, blockchain, Internet of Things, and their applications in business innovation. The course equips students with the knowledge to evaluate technological trends and leverage them for competitive entrepreneurial advantage.

Entrepreneurship and Value Creation: This course provides an in-depth exploration of the processes involved in creating and delivering value through entrepreneurial activities. Emphasis is placed on understanding customer needs, designing value propositions, and developing sustainable business models that generate economic, social, and environmental value in competitive markets.

New Product Development: This course introduces the systematic approach to developing new products, from ideation through market launch. Students will learn about product lifecycle management, user-centered design, prototyping, and agile methodologies. The course emphasizes innovation, risk management, and strategies for successful product commercialization.

Entrepreneurial Finance: This course provides foundational knowledge of financial principles and practices critical to entrepreneurial ventures. Topics include capital acquisition, financial planning, startup valuation, budgeting, and managing financial risks. The course prepares students to make informed financial decisions that support the growth and sustainability of new enterprises.

Foundations of Business: This course is a basic overview of the functional areas of business. It provides a general framework for understanding the development, structure, and social responsibility of business. Emphasis is placed on the interaction of management, marketing, finance, and operations within the business environment.

Principles of Marketing: This course focuses on the principles of marketing. The course contributes to technical and professional preparation in marketing, written and oral communication skills, understanding the global impact on business organizations, ethics in business, legal issues in organizations, role of cultural diversity in business and the dimensions of quality in organizations.

Business Communication: This course emphasizes on selecting the appropriate information, organization, and style to communicate effectively to a specific audience such as a supervisor, colleague, consumer or client. Written, oral, and team communication strategies will be explored and developed. Students will conduct primary and secondary research to identify career interests, practical job skills, and begin a “job search” portfolio that will include a working resume and cover letter.

Introduction to Business Law: The course material will provide the student with an overview of essential legal issues as they pertain to business: conflict resolution (litigation and alternatives); contracts; financing, securities and bankruptcy; legal entities and employment law; legal rights and obligations for business owners, officers, employees, directors and shareholders; intellectual property.

Data Driven Decision Making: This course covers a variety of data driven decision making topics for the purpose of making better strategic business decisions. Topics include BI tools and data analytics, with emphasis on predictive analytics focused on information and knowledge pertaining to customers, competitors, internal operations, and external variables.

Advanced Python: This course provides an in-depth exploration of advanced Python programming concepts beyond foundational syntax. It emphasizes sophisticated language features such as decorators, generators, context managers, and metaprogramming. Students will develop skills in writing clean, efficient, and reusable code, as well as working with modules and packages for large-scale applications. The course also covers concurrency and parallelism to optimize performance. Through hands-on projects, students will apply advanced Python techniques to solve complex computational problems and automate workflows. Emphasis is placed on best practices for code documentation, testing, and debugging.

Object-Oriented Programming: This course introduces the core principles and methodologies of object-oriented programming (OOP), including encapsulation, inheritance, polymorphism, and abstraction. Students will learn to design modular and maintainable software systems using OOP concepts and popular design patterns. The course covers class hierarchies, interfaces, and object lifecycle management. Emphasis is placed on translating real-world problems into object-oriented solutions. Students will implement projects that demonstrate effective use of OOP to enhance code reusability, extensibility, and robustness. Additionally, the course discusses the integration of OOP with software development frameworks.

Data Structures & Algorithms Design: This course provides a comprehensive understanding of fundamental data structures such as arrays, linked lists, stacks, queues, trees, graphs, and hash tables. Students will learn algorithm design techniques including recursion, divide and conquer, greedy algorithms, and dynamic programming. The course emphasizes analyzing algorithmic efficiency using Big O notation and optimizing solutions for time and space complexity. Through coding assignments, students will implement and test algorithms in various problem-solving contexts. Theoretical concepts will be applied to practical challenges in searching, sorting, graph traversal, and network flows. Students will also explore trade-offs between data structure choices for specific applications.

Database Design and Analytics: This course introduces students to the principles of database design, including data modeling, normalization, and relational schema development. It covers Structured Query Language (SQL) for database manipulation and query optimization techniques. The course also explores the use of databases in data analytics, including aggregation, filtering, and reporting functions. Students will learn how to design scalable databases that support transactional integrity and data consistency. Emphasis is placed on understanding data warehousing, business intelligence tools, and the extraction of actionable insights from large datasets. Hands-on projects will involve creating databases and performing analytic queries to support business decision-making.

Web Programming and App Development: This course provides comprehensive training in developing interactive and responsive web applications. It covers front-end technologies such as HTML, CSS, and JavaScript, along with back-end frameworks and server-side programming. Students will learn web protocols, RESTful services, database connectivity, and session management. The course emphasizes user experience design, accessibility, and cross-platform compatibility. Students will build full-stack web applications, integrating front-end interfaces with back-end services and databases. Deployment and maintenance of web applications in real-world environments are also discussed. Security considerations and best practices for web development are incorporated throughout the course.

Introduction to AI/ML: This course introduces foundational concepts in artificial intelligence and machine learning, including problem-solving, knowledge representation, and reasoning techniques. Students will study supervised, unsupervised, and reinforcement learning algorithms, including decision trees, clustering, and neural networks. The course emphasizes model training, evaluation, and tuning to improve predictive accuracy. Practical applications in areas such as natural language processing, computer vision, and recommendation systems are examined. Students will gain experience using popular AI/ML tools and libraries through hands-on projects. Ethical considerations and the societal impact of AI technologies are also explored.

Information Security: This course provides a thorough overview of information security principles and practices designed to protect digital assets. Topics include cryptography, network security protocols, threat modeling, vulnerability assessment, and incident response. Students will learn about access control, authentication mechanisms, and security policy development. Emphasis is placed on current cybersecurity challenges and strategies to mitigate risks. The course also covers legal and ethical issues related to information security. Through practical exercises, students will develop skills in securing computer systems and networks against attacks. Risk management and business continuity planning are integral components of the curriculum.

Introduction to Networking: This course introduces the fundamental concepts of computer networking, including the OSI and TCP/IP models, data transmission, and network protocols. Students will explore wired and wireless communication technologies, addressing, routing, and switching. The course covers network design, configuration, and troubleshooting techniques for local area networks (LANs) and wide area networks (WANs). Hands-on labs provide experience with configuring network devices and monitoring traffic. Security aspects such as firewalls and VPNs are also discussed. The course prepares students to understand network infrastructure critical for modern information systems.

System Architecture and Integration: This course provides a detailed study of computer system architecture, focusing on processor design, memory hierarchy, and input/output systems. Students will examine the interaction between hardware and software components and the integration of subsystems for optimized performance. Topics include instruction set architecture, pipelining, parallelism, and system buses. The course also covers operating system roles in resource management and system integration challenges. Students will gain hands-on experience in system configuration and performance analysis. Emphasis is placed on designing scalable and interoperable systems to support complex computing needs.

Cloud Computing: This course introduces the principles and technologies underlying cloud computing, including service models (IaaS, PaaS, SaaS) and deployment models (public, private, hybrid). Students will explore virtualization, cloud storage, and resource management techniques. The course covers cloud security, compliance, and cost optimization strategies. Hands-on exercises involve working with major cloud platforms to deploy and manage scalable applications. Students will learn about cloud-native architectures, containerization, and microservices. The curriculum emphasizes leveraging cloud technologies for business agility, innovation, and digital transformation.

Foundations of Statistics: This course provides a comprehensive introduction to the fundamental concepts and methods of statistics. It covers descriptive statistics, probability theory, and inferential techniques including hypothesis testing and confidence intervals. Students will learn to summarize and interpret data effectively, understand sampling distributions, and apply statistical reasoning to real-world problems. The course emphasizes the use of statistical software for data analysis and visualization. Applications across diverse fields such as business, engineering, and social sciences are highlighted. Critical thinking about data quality and statistical validity is also developed.

Linear Algebra: This course introduces the core concepts and techniques of linear algebra essential for scientific computing and applied mathematics. Topics include vector spaces, matrices, determinants, eigenvalues, eigenvectors, and systems of linear equations. Students will learn to perform matrix operations, understand linear transformations, and apply these concepts to solve practical problems in engineering, computer science, and data analysis. Emphasis is placed on both theoretical foundations and computational methods. Applications to areas such as computer graphics, optimization, and machine learning are also explored.

Discrete Mathematics: This course provides a thorough introduction to the mathematical structures and techniques fundamental to computer science and information technology. It covers logic, set theory, combinatorics, graph theory, and discrete probability. Students will develop skills in mathematical reasoning, proof techniques, and problem-solving strategies applicable to algorithms and computing systems. The course emphasizes the application of discrete mathematics in areas such as cryptography, network design, and software development. Practical exercises enhance understanding of abstract concepts and their real-world relevance

Digital Business & Tech Innovation- Concentration

This concentration equips students with the knowledge and skills to lead digital transformation and drive innovation through emerging technologies. Students explore digital business models, platform strategies, user experience design, and the application of disruptive technologies such as blockchain, AI, and cloud computing. The program prepares future leaders to strategically manage digital innovation and create scalable, tech-enabled solutions in a rapidly evolving global market.

Enterprise Strategy and Innovation Management: This course explores the strategic management of innovation within entrepreneurial and established enterprises. It focuses on how firms create, capture, and sustain value through innovation. Students will analyze business models, competitive positioning, strategic foresight, and innovation ecosystems to develop long-term strategies in dynamic markets.

Startups & Strategic Partnerships: This course examines how startups form and manage strategic partnerships to accelerate growth, access resources, and build competitive advantage. Topics include alliance formation, corporate venture capital, startup-corporate collaborations, co-creation models, and international partnerships. Real-world case studies highlight both opportunities and challenges of strategic partnerships.

Agile Product Management: Focused on product development in fast-paced environments, this course teaches students to apply agile methodologies to manage the product lifecycle. Key topics include user stories, MVP development, sprint planning, product roadmaps, backlog management, and stakeholder communication. Students will gain practical skills in iterative product development using agile tools.

Design Thinking for Innovation: This course introduces students to design thinking as a human-centered approach to innovation. Students learn to identify user needs, ideate creative solutions, and prototype and test concepts rapidly. Emphasis is placed on empathy-driven design, cross-functional collaboration, and real-world problem-solving to foster innovation in products, services, and systems.

Strategic Technology Management: This course provides frameworks and tools for managing technology as a strategic asset. It covers technology road mapping, R&D investment, intellectual property, and emerging tech assessment. Students will learn how to align technology initiatives with organizational goals, assess innovation readiness, and lead technological change in business environments.

Capstone Project: Venture Lab
This course provides a practical, hands-on environment where students apply entrepreneurial concepts to develop and launch new ventures. It emphasizes experiential learning through team collaboration, ideation, market research, business model development, and pitching to potential investors. Students will engage in real-world problem-solving, prototype creation, and iterative testing of business ideas. The course fosters critical thinking, creativity, and decision-making skills essential for entrepreneurial success. It also introduces tools and techniques for managing startup risks and scaling operations. Emphasis is placed on reflective practice and continuous improvement throughout the venture development process.

Technological Entrepreneurship Concentration

Focused on the creation and growth of tech-driven ventures, this concentration empowers students to transform technological ideas into viable business opportunities. The curriculum emphasizes startup development, agile product management, strategic partnerships, and innovation strategy. Students learn how to identify market needs, develop disruptive solutions, and scale technology-based enterprises in competitive environments.

Digital Business Models & Platforms: This course examines how digital technologies enable innovative business models and platform-based ecosystems. Students will explore the dynamics of network effects, multi-sided markets, digital monetization strategies, and data-driven value creation. Case studies focus on leading digital companies and startups transforming industries through scalable digital platforms.

Digital Transformation Strategy: This course explores how organizations can leverage digital technologies to drive strategic transformation. Students will analyze frameworks for digital maturity, transformation roadmaps, change management, and emerging technologies such as AI, IoT, and cloud computing. The course emphasizes leadership, innovation, and strategy in navigating digital disruption.

User Experience (UX) and Interface Design: This course introduces principles and practices of user experience (UX) and user interface (UI) design with a focus on digital products and services. Students will learn user research, persona development, wireframing, prototyping, usability testing, and accessibility design. The course combines design thinking with hands-on UX/UI tools for creating intuitive and user-centric experiences.

Blockchain Applications in Business: This course investigates how blockchain technology is reshaping business operations, value chains, and trust systems. Topics include decentralized finance (DeFi), smart contracts, token economies, supply chain transparency, and data security. Students will evaluate blockchain use cases across industries and design blockchain-enabled solutions for entrepreneurial ventures.

Creativity and Business Innovation: This course empowers students to cultivate creativity and apply it to solve business challenges through innovation. It covers creative problem-solving frameworks, ideation techniques, and organizational practices that foster innovation. Students will engage in hands-on exercises and collaborative projects to develop innovative solutions with real-world business impact.

Entrepreneurship Capstone Project
This course serves as a culminating experience where students integrate knowledge and skills acquired throughout their program to design, develop, and present a comprehensive entrepreneurial project. Students undertake independent or team-based research to identify viable business opportunities, create detailed business plans, and demonstrate practical implementation strategies. The course emphasizes application of theoretical frameworks to real-world entrepreneurial challenges, including market analysis, financial planning, and operational considerations. Students will present their projects to faculty and industry professionals, gaining feedback and refining their ventures. This capstone fosters professional communication, strategic thinking, and innovation management.