Mini Projects For Mca Students Free Download ((FULL))
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To give you a sense of what the questions look like, here is an example from our mini-projects. The mini-projects are all based on AidData, a dataset containing information about donations between countries over time.
There are two reasons why this is an effective strategy. First, students feel less pressure to be extremely conservative in their first submission. Since they know they can always regain the lost points, they feel more free to experiment. They are more adventurous. Second, they learn a lot from redoing the same exercise again.
As a side note, I always found it surprising that assignments are graded, and students are not expected to redo the work without problems. It seems like such a missed opportunity! So, my students redo the work and have an opportunity to compare before and after. They can literally see the improvements with their eyes! Interestingly, this also leads students to be more critical of my recommendations! Many push back if they are not convinced that what I suggest makes sense, and sometimes for good reasons! If you ask students to do more work, they expect that additional work to be worth it.
Thanks for the post. When I was a TA for a programming lab back in the day I did a variant of this where I asked students to resubmit their assignments if they could think of a better way of solving the problem/ or if they wanted to try a different programming language, and get extra credit. I also would give an optional challenging addendum to the original problem just to get some more engagement who were more advanced with their programming.
There\u2019s a special assignment I have designed for my visualization course that I have been using successfully for a number of years. I call it \u201Cmini-projects\u201D. A mini-project is a project students can develop over 1 or 2 weeks. It\u2019s big enough to simulate nontrivial decisions designers have to make in real projects, and it\u2019s small enough to be carried out in a small amount of time. That is, it\u2019s efficient and effective.
Students receive two main \u201Cingredients:\u201D a data set and a set of \u201Cdata questions.\u201D The second ingredient is crucial from the pedagogical standpoint. We do not ask students to \u201Cvisualize data.\u201D We ask them to answer questions using data visualization. There are two advantages to doing that: (1) the effectiveness of a solution can be verified more easily and (2) the results of the students can be compared on equal ground. To understand why this is true it suffices to imagine what would happen if the assignment were more vague: \u201CYou students, visualize these data.\u201D How do you actually compare the results? How do you give feedback? How do students know how well they have done?
Once we receive all their solutions, we collect all the submissions in a shared slide deck, and we go through them one by one collectively when we meet in class (or on Zoom if we meet remotely). This is another crucial ingredient of mini-projects. Students are exposed to a lot of different solutions and see our comments in the context of these many solutions. Normally this type of session is very lively, and students ask lots of questions of the type: \u201CHow about this solution? How about that solution?\u201D or \u201CWhy do you think this is a better solution?\u201D or \u201CWhat happens if we change it this or that way?\u201D I guess you can easily imagine why this has a lot of value from the pedagogical standpoint. This image gives you a sense of what students produce when you ask them to solve this problem.
One interesting variation I tried multiple times is to have students work on their solutions in two phases: one where they submit sketches as solutions (designed by hand or using some digital drawing program) and one where they submit their coded version using d3.js. When doing that, we sometimes reviewed only the sketches together or the sketches one week and the final solutions the following week. Over time, I came to the conclusion that it\u2019s a bit of an overkill, but this can be adapted in many different ways.
If you want to get access to the instructions for our mini-projects, you can find them in this Google folder I created to share the methodology with everyone. This is still a bit rough, but it\u2019s good enough to start using it. My plan is to write a guide for instructors who want to use it in their own course and maybe a nice website. In the meantime, if you are interested in using it and want more guidance, feel free to contact me by commenting on this post. I would definitely like to see this adopted by many more people and also learn what works and what does not work.
Hi,
I am rolling out a similar course at my instituition. It has just completed 1 round with a batch of 46 groups of students (around the age of 18). Each group comprises about 20 students. Project is a 20% component. For this round, I have used the dataset from Kaggle. I am thinking of any possibility of KNIME holding a platform similar to Kaggle but have people submitting the Knime workflow and ranking their results? However, if it is to support learning, then the dataset should be suitable to achieve the learning outcome. One big challenge I face is to find suitable dataset that can help to achieve the learning outcome. We only teach simple data mining techniques in our course: K-means clustering, classification using Decision Tree and Naive Bayes, estimation using MLR. Any ideas or suggestions to the dataset or a good running of the project component?
Engineering education is a dynamic blend of theoretical knowledge and practical application. Mini projects stand as a cornerstone of this learning journey, offering students a chance to bridge the gap between classroom concepts and real-world scenarios. These projects not only nurture creativity and problem-solving skills but also provide a platform to dive into various engineering disciplines.
Mini projects hold a crucial role in the academic curriculum of engineering students. They serve several valuable purposes, contributing to holistic skill development and knowledge enhancement. Here are some key reasons why mini-projects are essential for engineering students:
Mini projects provide a platform for students to practically apply the theoretical concepts they have learned in their lectures. This application enhances their understanding of the subject matter and promotes deeper learning.
These projects offer a hands-on experience of working with tools, technologies, and equipment that are commonly used in the industry. This practical exposure is invaluable for future engineering careers.
Home Workout Assistant is one of the well-known mini project ideas for engineering students. Design an app or device that guides users through home workouts, tracking progress and suggesting exercises.
However, the diverse range of mini project ideas across different engineering disciplines ensures that students can explore their interests and gain exposure to various fields, ultimately becoming well-rounded and capable engineers. So, embrace these mini projects as opportunities for growth, innovation, and a deeper understanding of the fascinating world of engineering.
I understand the concept of giving students multiple opportunities to reach mastery, but I have seen the projects carry over from lesson 4 to lesson 7 and other lessons few years ago. I believe this functionality was available on the 2019-2020 curriculum. I am not sure why it was discontinued. Also, there is still the link icon on lesson telling us that it is part of a larger project. It would be great if this functionality is made available. -Thanks so much for all that you do!
I love this idea - do you find that students tend to choose appropriately for their levels? I usually adapt the rubrics provided to be used in Google Classroom. I wonder how that would work for leveled projects. Makes me wonder if they all could use the same rubric, but have varying checklists for what gets included at the different levels.
This would be the year. I would be a fully project-based social studies teacher. After reading every PBL book I could read and attending PBL sessions at a few summer conferences, I had a vision for a new way of teaching my subject. My third year of teaching would be the first year of an entirely project-based curriculum. I had seen positive results in the previous year after doing a PBL unit each semester and now I would build on that momentum with a new group of students.
I began with our district curriculum map and set up a five-week and a four-week project for each semester (two projects per quarter). As a social studies teacher, this felt pretty easy. I could chunk the standards by theme and time period and then center the entire project around those standards. I started with larger driving standards and then added layers of connecting concept standards and then embedding skill-based standards. I even added a column in my planning document for ELA standards my students would be using in their language arts class.
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