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One type of doctoral program that traditionally requires the completion of a dissertation is a Doctor of Philosophy (PhD) program. PhD programs are research-focused doctoral degrees that are designed to produce scholars in a particular academic discipline or professional field. The overarching goal of PhD study is to contribute new knowledge and understanding to the field through original research. For this reason, completing a dissertation is a core requirement of most PhD programs.

The dissertation is the culminating project of a PhD program where students conduct extensive independent research and scholarly work under the supervision of faculty advisors and dissertation committee members. Through the dissertation, PhD candidates demonstrate their ability to identify a research problem or question within their field of study, conduct a comprehensive review of relevant literature, utilize appropriate research methods and analysis, and make an original contribution to the body of knowledge in the discipline. Dissertations generally take 1-3 years of full-time work to complete after coursework is finished.

The dissertation process consists of several formal steps. Students first develop a dissertation proposal outlining their research question or hypothesis, literature review, methodology, and anticipated findings. This proposal must be approved by the student’s dissertation committee before research can begin. Once approved, students move forward with conducting the proposed research and analysis. Throughout this stage, regular meetings are held with advisors to discuss progress and receive guidance.

Upon completion of the research and analysis, students write a lengthy dissertation manuscript presenting all elements of the completed research project. The written dissertation typically ranges from 150-300 pages in length and includes an introduction, literature review, methodology section, results/findings, discussion/conclusion, and references. After the written dissertation is submitted, students must then defend their work orally during a dissertation defense meeting with their committee. The committee will ask questions and evaluate the quality and rigor of the student’s independent research and written work.

Upon passing the defense, making any required revisions or corrections, and gaining final approval from the dissertation committee and graduate school, the PhD candidate will have completed all requirements for the doctoral degree. The dissertation demonstrates to degree granting institutions that PhD graduates have reached the level of expertise required to independently and creatively conduct worthwhile, publishable research within their specialized field of study. It is considered a hallmark of PhD education and signifies that a student has achieved a distinct level of expertise beyond a master’s degree.

There are many specific PhD programs across various disciplines that require completion of a dissertation as the capstone project. Some common examples of doctoral programs requiring a dissertation include PhD degrees in various sciences like Chemistry, Biology, and Physics. In the social sciences fields, programs such as Psychology, Sociology, Political Science, and Economics all typically require an original dissertation as the culminating experience. Dissertations are also standard components of PhD degrees in many humanities fields including Philosophy, History, English, and Communications. Professionally-oriented PhD programs in areas like Education, Nursing, Social Work and Business also generally necessitate completion of an independent research dissertation on a specialized topic within the given professional domain.

While dissertation requirements and formats vary some between individual doctoral programs and research topics, the multi-step process of developing a proposal, independently conducting original research using accepted methods, writing a lengthy manuscript, and defending the work publicly remains consistent across most academic PhD programs in the United States. The dissertation allows emerging scholars to make an authentic research-based contribution to their specialized field of study under the guidance of faculty experts before earning their doctoral degree. It is truly the pinnacle requirement demonstrating a student’s readiness to independently contribute to their discipline at the highest level as a credentialed PhD.

A dissertation is the defining component of most PhD programs across various academic disciplines in the United States. Through the rigorous multi-stage process of developing, conducting, writing, and publicly defending a substantial piece of original research, doctoral students complete the most complex and career-defining project of their education. Earning a PhD through successful dissertation work signifies that a graduate has reached the peak of expertise in their specialized academic or professional domain and is prepared to independently further advance their narrow field of study through future scholarship and research. The all-encompassing dissertation experience is truly the hallmark final step separating master’s and PhD education.


Microsoft launched its AI for Good initiative in 2017 with the goal of using artificial intelligence technology to help address major societal challenges. Some of the key challenges the program focuses on include:

Improving Global Health Outcomes – One of the primary focuses of AI for Good is applying AI to help improve health outcomes worldwide. This includes using machine learning models to help accelerate medical research and discover new treatments. For example, Microsoft is working with researchers to use AI to analyze genetics and biomedical data to help develop personalized medicine approaches. AI tools are also being developed to help tackle global health issues like improving early detection of diseases. By helping medical professionals more accurately diagnose conditions, AI could help save more lives.

Addressing Environmental Sustainability – Another major challenge AI for Good works on is supporting environmental sustainability efforts. Microsoft is developing AI solutions aimed at issues like monitoring climate change impacts, improving agricultural sustainability, and aiding conservation efforts. For example, computer vision models are being used with satellite imagery to track changes to forests, glaciers and other natural areas over time. AI is also being applied to help farmers optimize crop yields while reducing water and land usage. By aiding environmental monitoring and more efficient resource management, AI for Good’s goal is to help address the threat of climate change and encourage sustainable practices.

Improving Education Outcomes – Gaps in access to quality education is another societal problem AI for Good seeks to help solve. Microsoft is researching how to apply AI to personalized learning approaches and make education more widely available. This includes developing AI teaching tools and adaptive learning software that can tailor lessons to individual students’ needs and learning styles. Natural language processing is also being used to help automate essay grading and feedback to enhance learning assessments. By helping expand access to customized, data-driven education approaches, AI for Good’s vision is to help improve learning outcomes worldwide, especially in underserved communities.

Fostering More Inclusive Economic Growth – More inclusive and sustainable economic development is another focus challenge area. AI solutions are being explored that can help address issues like accessibility of employment and workforce retraining needed for new skillsets. For example, Microsoft is researching how AI career coaches and virtual agents could provide personalized guidance to help jobseekers of all backgrounds. Computer vision is also being applied to tasks like manufacturing to automate certain physical jobs in a way that creates new types of employment, rather than replacement. By aiding the transition to emerging industries, AI for Good’s aim is to foster stronger, more shared economic prosperity.

Enhancing Accessibility for People with Disabilities – Applying AI to push forward accessibility efforts and expand opportunities for those with disabilities is another key goal. Microsoft is researching uses of AI like computer vision, speech recognition and intelligent interfaces to develop new assistive technologies. This includes exploring how AI could help the blind or visually-impaired better navigate environments and access digital information. AI is also being researched as a way to aid communication for those with mobility or speech impediments. By removing barriers and enhancing inclusion through technology, AI for Good seeks to uphold principles of accessibility and equal access.

Promoting More Responsible and Trustworthy AI – Ensuring the responsible, safe and fair development and application of AI itself is another core challenge area AI for Good was launched to directly address. Microsoft actively researchers issues like mitigating algorithmic bias, increasing transparency in machine learning models, and fostering more accountable and well-governed uses of emerging technologies. The company also helps other organizations apply principles like fairness, reliability and privacy through initiatives assisting with AI safety, management and oversight practices. By advocating for and supporting the development of trustworthy, well-managed AI, Microsoft’s program aims to help guide emerging technology advances in a way that properly serves and benefits humanity.

Through its AI for Good initiative Microsoft is applying artificial intelligence to help address major challenges across a wide range of areas including global health, environmental sustainability, education, economic opportunity, accessibility, and governance of AI itself. By fostering innovative, responsible and data-driven technological solutions, the program’s overarching goal is to promote more inclusive progress on issues that are important to people and the planet. AI for Good demonstrates how emerging technologies, guided by principles of trustworthiness and service to humanity, could help achieve societal benefits at a large scale. The initiative reflects Microsoft’s vision of building AI tools to help advance important challenges facing communities worldwide.


Transitional care programs aim to ensure continuity of care and prevent adverse outcomes when patients move from one care setting to another, such as from a hospital to home. Comprehensive transitional care programs typically include several core components to effectively facilitate this transition and reduce the risk of errors, rehospitalizations, or other issues.

The core components of an effective transitional care program include: comprehensive discharge planning, post-discharge follow up, medication reconciliation and management, patient and caregiver education and engagement, and care coordination. Let’s take a closer look at each of these elements:

Comprehensive discharge planning starts during the hospital stay and involves a thorough evaluation of the patient’s needs and living situation upon discharge. Social workers, nurses, and discharge planners work closely with the patient and family to develop an individualized discharge plan. This plan outlines the patient’s diagnosis, treatment course in the hospital, any pending tests or future appointments, instructions for care at home including medication management and follow up care, equipment needs, and availability of family/social support. Good discharge planning results in a clear communication of this plan to both the patient and their outpatient providers.

Post-discharge follow up is a crucial component to catching any issues early and preventing adverse events. This typically involves a nurse practitioner or physician assistant led visit or phone call within 3-7 days of discharge to assess how the patient is coping and managing at home. During this follow up, the care provider comprehensively reviews medications, checks vital signs and wound healing, answers any patient questions, and screens for signs of potential complications or deterioration in condition that may warrant physician follow up. Additional follow ups may be scheduled further out depending on the individual’s needs.

Medication reconciliation involves compiling an accurate list of all prescription medications, over-the-counters, and supplements a patient is taking and comparing this to what is documented in medical records at each transition point. During care transitions, medications are clarified, reconciled, and reported to ensure no errors in dosages or discontinuations occur, and that the discharge instructions are synchronized across all providers. Pharmacists typically take the lead on medication reconciliation during transitions, but nurses and other clinicians also conduct reconciliations.

Patient and caregiver education and engagement is a critical process whereby key information is effectively communicated to promote self-management at home. During the hospitalization and in follow up sessions, clinicians spend dedicated time training patients and families on diagnoses, medication purposes and side effects, activity recommendations, diet, wound/incision care, when to seek help based on symptoms, and health maintenance. Teaching methods are tailored to individual health literacy needs. This facilitates carrying out the discharge plan successfully.

Care coordination ensures all members of the care team are aligned and that patients experience a seamless transition between settings without duplication or gaps in care/information. Formal care coordinators, often nurses or social workers, are designated to communicate with inpatient/outpatient providers, track test results and appointments, troubleshoot barriers, and serve as the single point of contact for patients as issues arise post-discharge. EHR systems further bolster care coordination by giving all providers updated, consolidated views of treatment plans and status.

Additional supportive elements in many transitional care programs include home health monitoring technologies that allow clinicians to maintain visibility into patients’ conditions from afar, telephone/telehealth capabilities for virtual follow up visits to limit travel demands, extensive support for obtaining any needed durable medical equipment or home services, and 24/7 access to clinicians for urgent questions/problems beyond regular business hours. Social determinants that could disrupt care transitions like transportation, housing instability andaffordability of medications/care are also addressed proactively.

The outcomes of comprehensive transitional care programs demonstrate reduced rates of preventable rehospitalizations, Emergency Department visits and healthcare costs through early detection and management of post-discharge issues. Patients also report high satisfaction with clarity of communication and organizational support received during care transitions. As healthcare delivery continues prioritizing value over volume, transitional care models play an important role in maintaining quality while keeping patients healthy in their home environments.

The key components of an effective transitional care program including thorough discharge planning, timely post-discharge follow up visits, medication reconciliation, patient education, care coordination across providers, use of remote monitoring technologies, addressing social factors, and availability of 24/7 clinician support. Together, these elements work to ensure patients experience safe, efficient transitions between care levels with their medical needs met.


Nike’s Capstone program provides high school students with an opportunity to develop important hard and soft skills that will serve them well both in future educational pursuits and career paths. Through this program, students work in teams on a real-world project proposed by Nike to help solve a business challenge. This hands-on experience allows students to gain valuable project management, collaboration, communication, and problem-solving abilities.

Some of the key skills students are able to hone through the Capstone program experience include:

Project Management Skills – Students learn what it takes to successfully plan and execute a complex project from start to finish. They have to define project goals and scope, develop a work plan with timelines and assign responsibilities, track progress, and ensure the project is delivered on schedule and meets requirements. This teaches skills like priority setting, resource allocation, and adapting to changes that are critical for any career.

Collaboration Skills – As members of multidisciplinary teams, students learn effective collaboration techniques for working together toward a common goal. They practice clear communication, active listening, consensus building, handling conflicts constructively, and tapping the diverse strengths each person brings. Participating in team-based problem solving readies students for the many collaborative work environments they will likely face.

Communication Skills – Both oral and written communication skills are sharpened through delivering project presentations and documentation. Students practice organizing information logically, adapting messages for different audiences like clients or stakeholders, and using various media like slides, reports and demonstrations. Delivering persuasive recommendations enhances presentation and public speaking confidence.

Problem Solving Skills – The real-world business challenges provided by Nike require innovative thinking. Students have to analyze complex problems from multiple angles, brainstorm creative solutions, conduct research, test ideas, and iterate based on outcomes. This strengthens critical thinking, research proficiencies, and the ability to tackle open-ended problems—skills integral to any career path.

Design Thinking Skills – Many Capstone projects involve designing new product concepts, prototypes or user experiences. This immerses students in the full iterative design process of empathizing with user needs, defining the problem, ideating solutions, prototyping, testing, and refining based on feedback. Students not only strengthen creative design skills but also learn human-centered approaches through practicing design thinking methodologies.

Research Skills – To thoroughly understand business challenges and solution spaces, students extensively research topics through literature reviews and primary data gathering like surveys, interviews and contextual inquiries. This improves their abilities to efficiently gather, assess validity of, synthesize and apply information from diverse sources—all key attributes of any research-driven career.

Time Management Skills – With tight deadlines and competing priorities across classes, activities and personal lives, students experience the importance of self-discipline, prioritization, planning and organizational abilities needed to effectively manage workload and schedules. The program cultivates time management proficiencies central to work-life balance.

Leadership Skills – While working as a team, students alternate facilitating meetings, motivating others, resolving conflicts, delegating responsibilities, setting examples and driving projects forward under constraints and ambiguity. Even those who may not be formal group leaders gain exposure to developing leadership presence and guiding successful team efforts.

Perseverance – Taking on open-ended challenges that may encounter setbacks along the way builds students’ perseverance, willingness to learn from mistakes/failures, and determination to find solutions—all qualities needed to progress in uncharted problem spaces. The hands-on work gives students confidence to push through obstacles and iterative approaches to continuous improvement.

The diverse hard and soft skills strengthened through participating in Nike’s high-impact Capstone program provide a strong foundation for whatever future studies or careers students may pursue. The real-world, collaborative project experience equips students to become flexible, resourceful problem solvers ready to excel in dynamic, fast-paced work environments of the future.


A policy analysis project and a program evaluation project are both common types of research and analytical projects that are undertaken in the public sector and in organizations that deliver public services. There are some key differences between the two in terms of their focus, goals, and methodology.

Policy analysis can be defined as the use of analytical tools and approaches to systematically evaluate public policy issues and potential solutions. The goal of a policy analysis project is to provide objective information to decision-makers regarding a policy issue or problem. This helps inform policymaking by assessing alternative policy options and identifying their likely consequences based on empirical research and impact assessment. Policy analysis projects typically involve defining and analyzing a policy issue or problem, outlining a set of alternative policy solutions or options to address it, and then assessing and comparing these alternatives based on certain criteria like cost, feasibility of implementation, impact, and likelihood of achieving the desired policy outcomes.

In contrast, a program evaluation project aims to systematically assess and provide feedback on the implementation, outputs, outcomes and impacts of an existing government program, initiative or intervention that is already in place. The key goal is to determine the effectiveness, efficiency and overall value of a program that is currently operational. Program evaluation uses research methods and analytical frameworks to collect empirical evidence on how well a program is working and whether it is achieving its intended goals and objectives. It helps improve existing programs by identifying areas of strength as well as weaknesses, challenges or unintended consequences. Program evaluations generally involve defining measurable indicators and outcomes, collecting and analyzing performance data, conducting stakeholder interviews and surveys, cost-benefit analysis, and making recommendations for program improvements or modifications based on the findings.

Some of the key differences between policy analysis and program evaluation include:

Focus – Policy analysis focuses on evaluating policy issues/problems and alternative solutions, while program evaluation assesses existing government programs/interventions.

Timing – Policy analysis is generally done before a decision is made to implement new policies, while program evaluation occurs after implementation to measure effectiveness.

Goals – The goal of policy analysis is to inform policymaking, whereas program evaluation aims to improve existing programs based on performance data.

Methodology – Policy analysis relies more on qualitative analytical techniques like issue scoping, option specification, impact assessment modeling etc. Program evaluation employs quantitative empirical methods like data collection, performance measurement, cost-benefit analysis etc. to rigorously test programs.

Recommendations – Policy analysis makes recommendations regarding which policy option is most suitable, while program evaluation provides feedback on how existing programs can be strengthened, modified or redesigned for better outcomes.

Audience – The audience and stakeholders that policy analysis reports target are typically policymakers and legislators. For program evaluation, the key audience includes program administrators and managers looking to enhance ongoing operations.

While there is some overlap between policy analysis and program evaluation, both serve distinct but important purposes. Policy analysis helps improve policy formulation, while program evaluation aims to enhance policy implementation. Together, they form a cyclic process that helps governments strengthen evidence-based decision making at different stages – from policy design to review of impact on the ground. The choice between undertaking a policy analysis project versus a program evaluation depends on clearly identifying whether the goal is exploring alternative policy solutions or assessing the performance of existing initiatives.

Policy analysis and program evaluation are complementary analytical tools used in the public policy space. They differ in their key objectives, focus areas, methods and types of recommendations. Understanding these differences is crucial for government agencies, think tanks and other organizations to appropriately apply these approaches and maximize their benefits for improving policies and programs.