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ePortfolio Template Database

Transcript: The foundation of an ePortfolio is critical to ensure it can: ePortfolios can be defined as: "personalized, Web-based collections of work, responses to work, and self-reflections used to demonstrate key skills and accomplishments for a variety of contexts and time-periods," as defined on the website. In Summary. . . It requires each ePortfolio author to use it as an administrative tool, so they can manage and organize the work they create for all different applications. The author is in total control of who can ultimately see the work. The foundation (structure) of an ePortfolio is very similar to that of a database! When "building" a master template for the ePortfolio we must ensure that all components are contained within the template - not unlike a database. Based upon the requirements of each Hospitality Instructor, components not needed can easily be hidden for that course. When hidden, they are only viewable by the author, not the end user. They can be reinstated by the author at any time - and expanded for the student's additional coursework in other classes. How does an ePortfolio compare to a database? Provide a digitized collection of artifacts, including text-based, graphic, or multimedia elements archived on a website or on other electronic media such as a CD-ROM or a DVD. An administrative tool that manages and organizes the students' coursework created with different applications and allows them to control who can see the work. Why the proper foundation (or navigation structure) is critical for creating an common ePortfolio template. The Importance of a Common ePortfolio Template How do we define an ePortfolio?

Database Diagram

Transcript: Datawise Model 1. Organize for Collaborative Work Goal: Set up culture of collaboration and open discussion for purposes of increasing student achievement. Hattie: High Influence of Collective Teacher Efficacy "Teachers who believe they can teach all children in ways that enable them to meet high standards are more likely to exhibit teaching behaviors that support this goal." - Nancy Protheroe, 2008 1. Organize for Collaborative Work 2. Build Assessment Literacy 2. Build Assessment Literacy Goal: Establish accurate concept of feedback "How do you use data to drive instruction?" CFA & Multiple modes of assessment "How do you know your students are learning?" "How do your students know that they are learning?" Dylan William: Feedback is only successful if students use it to improve their performance. 3. Create Data Overview Goal: Look at school from a broad lens and then narrow scope to specific barriers to student success. Choose a focus area(s) to study Ended 2017-2018 School year with a Gap Analysis to self-analyze barriers to student success. Knowledge barrier Motivation barrier Organization barrier Look at various data points in 2017-2018 data to substantiate claims made by gap analysis & formulate action plans "Be clear about the problem you want to solve before coming up with solutions" 3. Create Data Overview 4. Dig into Data Goal: Determine appropriate common formative assessments to use for informing instructional changes; analyze results of this data Google Drive library of cohort-specific CFA's Expose teachers to capabilities of EADMS Online Assessment Tools While CAASPP, PSAT, and other "big test" data is important to look at, aim is to look at shorter-term formative assessments that lead to instructional change(s) 4. Dig into Data 5. Examine Instruction Goal: Use evidence from data to make informed decisions on (curriculum and) instruction Sharing of best practices --> based on data Protocol for Examining Data 1. What parts of this data catches your attention? 2. What does the data tell us? What does the data NOT tell us? 3. What good news is there to celebrate? 4. What are the problem(s) of practice suggested by the data? 5. What recommendations does the team have for addressing the problem of practice? 5. Examine Instruction 6. Develop Action Plan 6. Develop Action Plan Goal: Use evidence from data to make informed decisions on (curriculum and) instruction Develop an action plan based on data story and instructional analysis. Four steps: 1. Decide on an instructional strategy - based on analysis of data & instruction. Set SMART goal(s) 2. Agree on what your plan will look like in classrooms - Have a shared understanding of what it looks like in a classroom 3. Put the plan in writing - Assign roles and responsibilities as well as time lines 4. Decide on how you will know the plan is working - "What does success look like?" 7. Plan to Assess Progress 7. Planning to Assess Progress Goal: Use evidence from data to make informed decisions on (curriculum and) instruction What assessments will be used to measure progress? Short-Term Data Classwork and Homework Observing students' participation Asking students about their learning (feedback) Medium-Term Data Cohort-specific Common Formative Assessments DIA's and other Benchmarks Long-Term Data CAASPP? CAST? EOY Grades? Cohort Plan 8. Act and Assess 8. Act and Assess Goal: Use evidence from data to make informed decisions on (curriculum and) instruction Are we all on the same page? Are we doing what we said we'd do? Are our students learning more? Where do we go from here? This step is where process becomes cyclical. Through constant revisiting of short- (and medium-) term assessments, informed decisions on instructional changes can be made to get to learning goals

Database Project template 1

Transcript: Key Tables In 2014, one of the largest automobile company in US faced the major recall. According to NHTSA 27 million cars were recalled. NHTSA failed to detect this issues in GM models due to the discrete nature of the data and good quality analysis. Prof Chaiyaporn Mutsalklisana By Team Ultron Vihar Raul Pranay Sampat Ritiksha Gada Ruchi Goyal Introduction Objective Stored Procedures Our model also encorporate database concepts of views and indexes. Car Details View Car Event Count View (encorporated outer join) Car Accident Count View Indexes: Indexes on transaction table for performance enhancement of query. Views And Indexes Manufactured Car Table : Car details, assembly details, components used. Car Registration : Registration and ownership details. Event Table : Events accociated with registered car (accident, component issues,driving quality issues etc) Accident Table : Car accident and factors related to it. Triggers EER Diagram Queries and Subqueries This query will state car registration details (License Plate, Owner Details), accident details(Cause, Zones), car details (Engine and chassis number).This is an adjustable query where you can extract records for particular accident, particular car, particular model, perticular vehicle type. THANK YOU Predictive Analysis To Avoid Car Recalls Aim of our model is to analyse the defects from root cause level for various events such as accidents,manufactring and assembly defects to attain sustainable production. Our model will help reduce the revenue losses to manufactring company due to car recalls, minimize the defects and maximize the safety of customer. Model Activity Tracker: Whenever a new car model is created, recored get inserted into activity tracker for that model. Accident Tracker: Whenever a new accident is reported.Count of accident is increased in activity tracker. Event Tracker: Whenever a new event is reported.Count of event is increased in activity tracker. Data Entry Procedure: To store the data in sanity and structured manner. Event Procedure: To find events for a particular model and their causes along with the zones where events occured. AccidentProcedure: To find accident for a particular model and their causes along with the zones where events occured.

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