Tag Archives: capstone

HOW DO INTERIOR DESIGN PROGRAMS TYPICALLY ASSESS AND EVALUATE CAPSTONE PROJECTS

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Interior design capstone projects are usually the culminating experience for students near the end of their program, acting as a way for students to demonstrate their comprehension and integration of everything they have learned. These large-scale projects are intended to simulate a real-world design process and commission. Given their importance in showcasing a student’s abilities, interior design programs put a significant amount of focus on thoroughly assessing and providing feedback on capstone projects.

Assessment of capstone projects typically involves both formative and summative evaluations. Formatively, students receive ongoing feedback throughout the entirety of the capstone project process from their design instructor and occasionally other faculty members or design professionals. Instructors will check in on progress, provide guidance to help address any issues, and ensure students are on the right track. This formative feedback helps shape and improve the project as it comes together.

Summative assessment then occurs upon project completion. This usually involves a formal presentation and portfolio of the completed work where students demonstrate their full solution and design development process. Faculty evaluators assess based on pre-determined rubrics and criteria. Common areas that rubrics cover include demonstration of programming and code compliance, appropriate design concept and theming, selection and specification of materials and finishes, clear communication of ideas through drawings/models/renderings, and organization and professionalism of the presentation.

Additional criteria faculty may consider include the level of research conducted, appropriate application of design theory and principles, creative and innovative thinking, technical skills shown through drawings/plans, accuracy and feasibility of specifications, comprehension of building codes and ADA/universal design standards, demonstration of sustainability concepts, budget management and how the project meets the needs of the target user group. Strengths and weakness are analyzed and noted.

Evaluators often provide written feedback for students and assign a letter grade or pass/fail for the project. Sometimes a panel of multiple faculty members, as well as potentially industry professionals, will collectively assess the capstone presentations. Students may be called on to verbally defend design decisions during the presentation question period as well.

The capstone experience is meant to holistically demonstrate the technical, practical and creative skills interior designers need. Programs aim to simulate real consultancy work for clients. Assessment emphasizes how well the student operated as an independent designer would to take a project from initial programming through to final design solutions while addressing all relevant constraints. Feedback and evaluation focus on professionalism, attention to detail, competence in key areas as well as the overall effectiveness and polish of the final presentation package.

Recording rubrics, grading criteria and individual written feedback allows programs to consistently measure skills and knowledge demonstrated by each student completing a capstone project. It also provides opportunities for growth – students can learn from both strengths and weaknesses highlighted. Aggregate program assessment data from capstone evaluations further helps faculty determine if broader curriculum or pedagogical adjustments may be beneficial. The thorough and multifaceted assessment of interior design capstone projects acts as an important culminating evaluation of student learning and competency prior to graduation.

Interior design capstone projects are intended to simulate real-world design processes and commissions. Assessment involves formative feedback throughout as well as summative evaluation of the final presentation based on predetermined rubrics. Areas covered include programming, concept/theming, materials/finishes, clear communication, research conducted, design principles applied, creative/innovative thinking, technical skills, specifications/feasibility, codes/standards, sustainability, budgeting, meeting user needs and overall professionalism. Multiple evaluators provide written feedback and assign grades/ratings to gauge student competency in key designer skills upon completing their studies.

WHAT ARE SOME RECOMMENDED CODING TOOLS FOR MIDDLE SCHOOL STUDENTS TO USE FOR THEIR CAPSTONE PROJECTS

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Scratch is one of the most popular and widely used coding tools for younger students and would be suitable for many middle school capstone projects. Developed by the Lifelong Kindergarten group at the MIT Media Lab, Scratch allows students to program by dragging and dropping blocks of code to create interactive stories, games, and animations. It uses a visual, block-based programming language that does not require students to know any text-based syntax. This makes it very accessible for beginners. Scratch’s online community is also very active and encourages sharing of projects, which could help students get feedback and ideas on their capstone work. The platform is freely available at scratch.mit.edu.

Another good option is App Lab from Code.org. App Lab allows students to code games, animations and more using a simple drag-and-drop interface very similar to Scratch, but is web-based rather than a downloaded application. It also integrates with Code.org’s larger suite of curriculum and courses, which teachers can leverage for lesson planning and project ideas aligned to state standards. Like Scratch, App Lab has a large online sharing community as well. An advantage it has over Scratch is the ability to more easily add features like sound, images and interaction with device hardware like the camera. This could allow students to create more robust apps and games for their capstone project.

For students looking to do more complex programming beyond drag-and-drop, another recommended tool is Microsoft MakeCode. MakeCode has editors for creating projects using JavaScript/TypeScript, as well as specialized versions for microcontrollers like micro:bit and Circuit Playground Express that allow physical computing projects. The JavaScript editor in particular could work well for a more advanced middle school capstone project, as it allows for coding things like websites, games and more using real code. Many of Code.org’s courses are also compatible with MakeCode which can provide structure and ideas. The community is also very active online to help students with challenges. MakeCode allows students to share and remix each other’s projects too.

If the capstone involves hardware projects, the physical computing versions of MakeCode like micro:bit and Circuit Playground Express are excellent choices. These allow students to code microcontrollers to control lights, motors, sensors and more using block and text-based languages. This could enable projects like data logging devices, robots, interactive art installations and more. Both include extensive libraries of sample projects and are designed to be very beginner friendly. They also have large learning communities online for help and inspiration.

Another good programmable hardware option is littleBits. littleBits are magnetic snap-together electronic blocks like buttons, LEDs, motors and sensors that connect together using the contact points. The blocks can then be programmed by dragging color-coded magnetic wires between power, input and output blocks. This allows hands-on physical computing and circuitry projects without needing to solder or know electronics. Kits include pre-made project examples as well as an online library of community projects. Since there is no screen, littleBits is best combined with another coding tool if an interactive program is desired. It opens up many options for physical computing and tinkering types of projects.

All of these recommended tools – Scratch, App Lab, Microsoft MakeCode, micro:bit, Circuit Playground Express and littleBits – are suitable options for engaging middle school students in coding and leveraging the constructionist learning approach of learning by making capstone projects. When selecting a tool, considerations should include students’ experience levels, the type of project being undertaken, availability of resources, and how well a tool aligns to curriculum standards. Teachers can also find additional tools that work well, these provide a solid starting point and have large user communities for additional support. The most suitable tool will depend on each unique situation, but these are excellent choices to explore for computer science learning through personally meaningful capstone work.

HOW DO CAPSTONE PROJECTS IN HEALTHCARE ADMINISTRATION BENEFIT THE STUDENTS AND THE HEALTHCARE SYSTEM

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Capstone projects are a key component of most healthcare administration degree programs as they provide invaluable real-world experience to students before they graduate and enter the job market. These large-scale projects give students the opportunity to apply the knowledge and skills they have learned throughout their studies to solve an actual problem or address an issue facing a healthcare organization. In the process, capstone projects benefit both students as well as the broader healthcare system in several important ways.

For students, capstone projects are a chance for them to gain hands-on experience taking on the type of complex management or strategic challenges they will likely encounter in their future healthcare careers. By working directly with a healthcare organization, students get exposure to the inner workings and day-to-day operations of facilities like hospitals, clinics, insurance companies, or public health departments. They also develop valuable soft skills like communication, critical thinking, project management, and leadership that are essential for success in healthcare administration roles. Having a substantive capstone project to highlight on their resume also gives students a competitive edge when job or graduate school applications. Perhaps most importantly, these projects allow students to apply classroom concepts in a real-world setting which deepens their learning and better prepares them to transition into the workforce.

In addition to benefiting students individually, capstone projects provide tangible value back to the healthcare organizations that host them. Host sites are able to leverage the dedication, fresh perspectives, and technical skills of driven students to take on projects that may otherwise go unaddressed due to busy schedules and limited internal resources. Examples of capstone projects undertaken for healthcare facilities include strategic plans, quality improvement initiatives, program evaluations, needs assessments, marketing campaigns, process improvement projects, and more. By dedicating resources to a capstone, organizations gain actionable insights and solutions related to some of their most pressing operational, financial, or patient care challenges. Some capstone projects have even led to the creation of new programs or services that genuinely improve patient outcomes and community health.

On a broader level, capstone projects also benefit the entire healthcare system. As future healthcare leaders and administrators, capstone experiences help ensure students graduate with applicable skills that align with the evolving needs of the industry. By taking on substantial projects that tackle real issues, students develop an in-depth understanding of the complex healthcare environment and the types of systemic problems facing providers, payers, and communities. They also establish valuable industry connections that can lead to job opportunities or collaborations after graduation. With each capstone completed, the healthcare system gains well-trained new graduates that hit the ground running, instead of requiring costly on-the-job training. This accelerates their contributions and helps alleviate workforce shortages in administrative roles.

There is also evidence capstone projects improve diversity, equity, and inclusion in healthcare administration. A study published in 2020 found female and minority students were more likely to use their capstone experience to address social determinants of health, cultural competency, or barriers marginalized groups face in accessing care. By surface these important issues, capstones helped sensitize a new generation of future leaders and shift the industry culture. Capstone hosts that serve vulnerable populations gain project outcomes centered on empowering underserved communities and reducing disparities.

The strategic application of classroom theories, development of practical skills, and cultivation of authentic healthcare experience capstone projects provide, substantially benefits both students as well as the larger healthcare sector. By connecting classroom to career and addressing real-world problems, capstones play a pivotal role in training innovative leaders ready to advance healthcare through sound administration and management. Both healthcare organizations and communities benefit from the fresh perspectives and solutions generated through years of student dedication to these high-impact culminating projects.

CAN YOU EXPLAIN THE PROCESS FOR COMPLETING A CAPSTONE PROJECT IN THE GOOGLE DATA ANALYTICS CERTIFICATE PROGRAM

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The capstone project is the final assessment for the Google Data Analytics Certificate program. It provides students the opportunity to demonstrate the skills and knowledge they have gained throughout the six courses by completing an end-to-end data analytics project on a topic of their choosing.

To start the capstone project, students will need to choose a real-world dataset and formulate a question they want to answer using data analytics. The dataset can be from an open source database, their own collection, or publicly available from the internet. It is recommended students select a topic they are personally interested in to stay motivated throughout the lengthy capstone project.

Once a dataset and question are chosen, students then begin the multi-step capstone project process. The first step is to discover and understand the data through exploratory data analysis techniques learned in the Exploratory Data Analysis course. This involves loading the data, assessing its quality, dealing with missing values, identifying patterns and relationships, and visualizing the data to gain insights. A short document summarizing the key findings from exploratory analysis is produced.

With a better understanding of the data, students then move to the next step of defining the problem more concretely. Here, they will state the business problem or research question more specifically based on exploratory findings. Well-defined questions help scope the rest of the capstone project work. Students may need to return to exploratory analysis with a revised question as understanding improves.

In the third step, students collect any additional data required to answer their question. This could involve web scraping, APIs, or combining external datasets. They document the sources and process for collecting additional data in a reproducible manner.

Armed with the question and collected data, students then build machine learning models to help answer their question in the predictive modeling step. They apply techniques from the Machine Learning course to prepare the data, select algorithms, tune parameters, evaluate performance and compare results. Graphs and discussion justify their modeling selections and parameter tuning decisions.

Next, students interpret the results of their predictive modeling and provide conclusions to their original question based on facts and evidence from their analysis. They discuss whether analysis supported or refuted hypotheses, identify limitations or caveats in conclusions due to limitations in data or modeling assumptions. Potential next steps for additional analysis are also proposed.

Throughout the process, clear documentation and code are essential. Students produce Jupyter notebooks to display each step – from data wrangling to visualizations to modeling. Notebooks should have explanatory comments and be well structured/modularized for clarity.

Students also produce a short paper summarizing their overall process and findings. This paper ties together the problem motivation, data understanding, methodology, results and conclusions. Visuals from the notebooks can be referenced. Proper writing fundamentals are expected regarding structure, grammar and effective communication of technical concepts for a lay audience.

Once complete, students submit their Jupyter notebooks containing code and visuals, along with the short summary paper for evaluation. Instructors assess a variety of factors including choice of problem/dataset, quality of analysis conducted at each step, documentation/notebooks, conclusions drawn, and communication of findings. Feedback is then provided to help students continue developing their skills.

Through this comprehensive capstone experience, students demonstrate the cumulative abilities and competencies expected of any data analyst. Namely – identifying meaningful problems, acquiring and cleansing relevant data, applying analytical tools and techniques, effectively communicating results and implications. It serves as a practical culminating project showcasing skills gained in the entire Google Data Analytics Certificate program.

The capstone project provides a structured yet open-ended process for students to combine all their learning into a complete data analytics workflow to solve a real problem. Though challenging, it equips them with project experience highly valuable for employment as practiced data professionals. Proper execution of this capstone is essential for mastering core competencies of the data analyst role.

CAN YOU PROVIDE EXAMPLES OF REAL WORLD DATASETS THAT STUDENTS HAVE USED FOR THE CAPSTONE PROJECT

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One of the most common types of datasets used is health/medical data, as it allows students to analyze topics that can have real-world impact. For example, one group of students obtained de-identified medical claim records from a large insurance provider covering several years. They analyzed the data to identify predictors of high medical costs and develop risk profiles that could help the insurance company better manage patient care. Some features they examined included diagnoses, procedures, prescriptions, demographics, and lifestyle factors. They built machine learning models to predict which patients were most at risk of future high costs based on their histories.

Another popular source of data is urban/transportation planning datasets. One project looked at public transit ridership patterns in a major city using anonymized tap-in/tap-out records from the city’s subway and bus systems. Students analyzed rider origins and destinations to identify the most traveled routes and times of day. They also examined how ridership changed on different days of the week and during major events. Their findings helped the city transportation authority understand demand and make recommendations on where to focus service improvements.

Education data is another rich area for capstone work. A group worked with a large statewide standardized test scores database containing student performance dating back over 10 years. They performed longitudinal analysis to determine what factors most strongly correlated with improvements or declines in test scores over time. Features they considered included school characteristics, class sizes, teacher experience levels, as well as student demographics. Their statistical models provided insight into what policies had the biggest impacts on student outcomes.

Some students obtain datasets directly from private companies or non-profits. For example, a retail company provided anonymous customer transactions records from their loyalty program. Students analyzed purchasing patterns and developed segments of customer groups with similar behaviors. They also built predictive models to identify good prospects for targeted marketing campaigns. Another project partnered with a medical research non-profit. Students analyzed their database of published clinical trials to determine what therapies were most promising based on completed studies. They also examined factors correlated with trials receiving funding or being terminated early. Their analyses could help guide the non-profit’s future research investment strategies.

While restricted real-world datasets aren’t always possible to work with, many students supplement private data projects with publicly available benchmark datasets. For example, the Iris flowers dataset, Wine quality dataset and Breast cancer dataset from the UCI Machine Learning Repository have all been used in student capstones. Projects analyze these and apply modern techniques like deep learning or make comparisons to historical analyses. Students then discuss potential applications and limitations if the models were used on similar real problem domains.

Some larger capstone projects involve collecting original datasets. For instance, education students designed questionnaires and conducted surveys of K-12 teachers and administrators in their state. They gathered input on professional development needs and challenges in teaching certain subjects. After analyzing the survey results, students presented strategic recommendations to the state department of education. In another example, engineering students gathered sensor readings from their own Internet-of-Things devices deployed on a university campus, collecting data on factors like noise levels, foot traffic and weather over several months. They used this to develop predictive maintenance models for campus facilities.

Real-world datasets enable capstone students to gain experience analyzing significant problems and generating potentially impactful insights, while also meeting the goals of demonstrating technical and analytical skills. The ability to link those findings back to an applied context or decision making scenario adds relevancy and value for the organizations involved. While privacy and consent challenges exist, appropriate partnerships and data access have allowed many successful student projects.