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26
Sep

Sabbatical 2018 Week 6: The Big Data Landscape is Ridiculously Huge

Last week I completed course two in the Big Data Specialization: Big Data Modeling and Management Systems. This was another very technical course. We gained an in-depth knowledge of why big data modeling and management is essential in preparing to gain insights from your data. We gained knowledge of real world big data modeling and management use cases in areas such as energy and gaming. We also learned to understand different kinds of data models, the ability to describe streaming data and the different challenges it presents, and the differences between a DBMS and a BDMS.

We did a lot of playing in the Cloudera VM again. I type in the codes given and things magically happen. It’s kind of cool, but no way I’m going to remember how to replicate any of this. For example, we learned how to import and query text documents with Lucene and perform weighted queries to see how rankings change. We learned how to perform statistical operations and layout algorithms on graph data in Gephi. I believe we actually installed and ran that program on our computers instead of in Cloudera. Then back in Cloudera we learned how to view semi-structured data streaming in real-time from a weather station and create plots of streaming weather station data.

If your head is spinning from just the few programs I mentioned already, it’s going to explode when you hear we also were introduced to Redis, Aerospike, AsterixDB, Solr, and Vertica. I thought I might pass out. The Big Data landscape is ridiculously huge. How anyone knows all of these programs is beyond me.

Also this week I reached out to district IT to schedule a meeting with the Canvas administrators to discuss Canvas Data Portal. It sounds like they have already started doing some exploring on their own. In fact, I was told to contact another individual who had already done some initial investigation in the use of Amazon Redshift. And a few developers have already explored it as part of a Transformation data project. It also looks like I’ll be able to get access to our Data Portal soon as well so I can start exploring. This is great news, as I thought this one step would be the one thing to derail my sabbatical proposal. Things are moving forward. I’m a little behind on my reading and annotated bib, but besides that I’m right on track. Yay, me!

 

 

 

25
Sep

Sabbatical 2018 Week 5: Not All Work and No Play

If you’ve never taken an extended sabbatical from your job, you’re really missing out. It’s a great experience that I’m grateful to have taken advantage of twice in my 20 years in Maricopa. I really think I’ve worked hard enough to deserve it, and you probably have too. According to the MCLI website,

“A sabbatical leave is an opportunity to broaden or deepen educational interests, to explore new areas, or examine instructional methods to enhance the mission of the college. A sabbatical leave gives faculty a respite from their normal duties in order to provide them an opportunity to grow professionally. The goal of a sabbatical leave project is to engage faculty in the areas of study, research, travel, work experience, or other creative activity, and to contribute to the institution as a whole upon his/her return to the college.”

If you’re into learning new things then a sabbatical in Maricopa is for you. However, in the more generic sense the word sabbatical, which can be a noun or an adjective, comes from the Greek word sabatikos, which means “of the Sabbath,” the day of rest that happens every seventh day. Most teaching jobs come with the promise of a sabbatical, which is a year of not having to teach, though you still get paid. It’s also interesting to know that only 5% of US companies offer paid sabbaticals. So I’m not complaining that I still have to work during my sabbatical. At least it’s something I’m interested in learning and doesn’t involve grading hundreds of essay. It’s definitely a respite from the norm.

The challenging part for me is getting used to doing less. Many faculty do more than just teach a 15 hours schedule, and Maricopa is good about providing opportunities and compensating those of us who do more. For the past 4 years, I’ve been wrapped up in the world of professional development, online learning and OER. I’ve taught very little, but worked more than I have in previous years collaborating, coordinating, and strategizing with our Instructional Designer, CTLE Staff, eCourses faculty lead and faculty developers. My involvement also included working district wide with other CTL directors, elearning and OER leaders. It’s hard to just go cold turkey and not talk to or work with any of those people anymore. My only saving grace is that many of those people are personal friends and we still chat when I sneak on campus to visit or attend a planned happy hour. Shout out to Meghan, my better half for the last 4 years.

One major plus is that my other partner in crime for the past 4 years, Dr. Lisa Young, is also on sabbatical this year, and her sabbatical proposal is similar to mine – Big Data. And as the Faculty Director of SCC’s CTL and Co-Tri-Chair of the Maricopa Millions project, she’s been involved in all the same things I have. So she can relate. Part of our sabbatical plan is to hike every other week to discuss our projects and other stuff. It’s comforting to know she’s learning the same things and good to have someone to bounce ideas off of. And it doesn’t hurt to get some exercise in on a regular basis. Below is evidence of our endeavors.

The best part of a sabbatical is you get to determine your schedule, so there’s a lot of flexibility in there for doing the things you never seem to have time for. The reality is that many of the people you’d like to do those things with are still working hard and stressed out. Ha! (Sorry Beth! Thanks for visiting me yesterday)

And one more for the road. So far we’ve hiked Holbert and Mormon Trails on South Mountain, Cholla Trail on Camelback, and Trail 100 in Dreamy Draw followed by breakfast at Dick’s Hideaway, Scramble, and First Watch. Breakfast is an added bonus. What is up with my hair?! Anyway, I’m looking forward to it cooling off so we don’t have to hike so early. Then sabbatical life will be truly perfect. Well, if they can figure out how to pay me correctly then it will be truly perfect.

12
Sep

Sabbatical 2018 Week 4: Where’s My Money?

I don't know image.It has become painfully clear that I will never be a data analyst. That’s not necessarily a bad thing considering I already have a job as an educator at a great community college. Thank goodness for that because I’m a little over my head here in my Big Data Specialization from the University of California San Diego. Somehow I’m learning just enough to get by, but don’t ask me anything specific. You really have to be a programmer to use this stuff.

Course 2 was Big Data Modeling and Management Systems and it was very technical. It was all about Big Data technologies, and frankly I’m happy to leave that part to the IT experts. Systems and tools discussed included: AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL <eyes glass over>. We learned an in-depth knowledge of why big data modeling and management is essential in preparing to gain insights from your data, and knowledge of real world big data modeling and management use cases in areas such as energy and gaming. We also learned about different kinds of data models, the ability to describe streaming data and the different challenges it presents, and the differences between a DBMS and a BDMS.

I some how managed to complete the final assignment for this course, which was to design a data model for a fictitious game: “Catch the Pink Flamingo.” The strangest thing about this whole Coursera setup is the assignments are peer reviewed. I’m awaiting my fate as I type. I wasn’t really clear if what I was doing was correct, but I did my best and submitted the assignment. Then I had to go in and review my classmates’ work. Yeah, right? It looked good. Nothing like mine, but hey, who’s right? I guess we’ll see once my assignment is peer reviewed.

Two courses down; four to go. Then on to the Johns Hopkins Data Science Specialization. In the mean time, I’ve reached out to our district IT person in charge of Canvas. I’m hoping to meet with her soon to discuss Canvas Data Portal. ITS has a proposal process when our resources are needed for more than 20 hours, so I have to go to the PMO site which is where a business case can be initiated to start the process. Additionally, the IITGC provides prioritization of business cases/projects for ITS, so I’ll have to cross my fingers and hope my case gets prioritized.

Okay, back to figuring out how to get paid correctly. Hey, Maricopa, where’s my money?

 

31
Aug

Sabbatical 2018 Week 3: What the Hadoop?

Coursera courseSo I finished my first Coursera course: Introduction to Big Data. It was the first and shortest of the 6 Big Data specialization courses. It was only a 3 week course. I added my course completion certificate to my LinkedIn profile, which needs to be updated. (hint hint)

I really like the reporting system in Coursera. I posted a screenshot that shows progress. It really helps the student know exactly where they are in the course and what needs to be done and when it needs to be done. If there is something to be done, it will be listed first with a Start button to quickly get to that part of the course, as you can see in the image. Makes me wish I had something like this for my students in my courses in Canvas.

The last part of this course had some programming. We got a short introduction to Hadoop and how to run the Wordcount program. Surprisingly this time I found playing in the Cloudera VirtualBox fun. Amazing how that is when you don’t run into errors and the programs work as expected. Or more accurately when there aren’t any user errors. I actually felt like I knew what I was doing. Maybe a little over confident, but eh, who cares.

I can’t imagine that I would remember the code to run the program: hadoop jar /usr/jars/hadoop-examples.jar wordcount in the future, but I do have good notes for future reference. And I’m still a little fuzzy about MapReduce, as initially I couldn’t see a good use for it in my work. Our last discussion in this class stumped me a bit: What are some examples in your work or daily life where applying the map reduce algorithm can speed up the process of the situation? Dang, that’s a good question. Ha! I guess I’m still trying to figure that one out beyond the basic sorting students by demographic data or past grades.

I’m also finishing week 4 of the second course: Big Data Modeling and Management Systems this week. Who knew there was so much to learn about data modeling. Data models deal with many different types of data formats. Streaming data is becoming ubiquitous, and working with streaming data requires a different approach from working with static data. So we are learning how to gain practical hands-on experience working with different forms of streaming data this week in this course.

30
Aug

Big Data & Analytics Annotated Bibliography

As part of my sabbatical, I need to gain a basic understanding of statistics and data structure and get an overall sense of what educational data analytics entails, so I did some research and created a short reading list of published articles and books to read. Last summer I read Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O’Neil as part of our learning analytics professional learning community (PLC) at GCC. I also started reading a few of the articles I found including Academic analytics and data mining in higher education and Educational Data Analytics Technologies For Data-Driven Decision Making In Schools.

I plan to add to this list as I go, so if you have any suggested articles or books you think I should read, send them my way. Over the course of this semester I will be reading and adding to my Big Data & Analytics Annotated Bibliography. I’ve created this post to share my work. I’ve also included my Appendix D: Reference/Reading list for Sabbatical below.

Big Data & Analytics Annotated Bibliography

Baepler, P., & Murdoch, C. (2010). Academic analytics and data mining in higher education.
International Journal for the Scholarship of Teaching and Learning, 4(2). doi:10.20429/
ijsotl.2010.040217

This essay links the concepts of academic analytics, data mining in higher education, and
course management system audits and suggests how these techniques and the data they produce
might be useful to those who practice the scholarship of teaching and learning. Academic
analytics, educational data mining, and CMS audits, although in their incipient stages, can
begin to sift through the noise and provide SoTL researchers with a new set of tools to
understand and act on a growing stream of useful data.

Appendix C

Sabbatical Reading List

Baepler, P., & Murdoch, C. (2010). Academic analytics and data mining in higher education. International Journal for the Scholarship of Teaching and Learning4(2). doi:10.20429/ijsotl.2010.040217

Delaware County Community College. (n.d.). Big data, algorithms, and predictive analytics – Learning analytics – LibGuides at Delaware County Community College. Retrieved July 13, 2017, from http://libguides.dccc.edu/learning_analytics/big_data

Herold, B. (2016, January 11). The future of big data and analytics in K-12 education – Education Week. Retrieved from http://www.edweek.org/ew/articles/2016/01/13/the-future-of-big-data-and-analytis.html

Lawson, J. (2015). Data science in higher education: A step-by-step introduction to machine learning for institutional researchers. Chico, CA.

Picciano, A. G. (2012). The evolution of big data and learning analytics in American higher education. Online Learning, 16(3). doi:10.24059/olj.v16i3.267

Reinitz, B. (2017, August 10). 2017 Trends and Technologies: Analytics. Retrieved from https://library.educause.edu/resources/2017/8/2017-trends-and-technologies-analytics

Sampson, D. G. (2016, October 22). Learning analytics: Analyze your lesson to discover more about your students – eLearning Industry. Retrieved from https://elearningindustry.com/learning-analytics-analyze-lesson

Sampson, D. G. (2016, October 20). Educational data analytics technologies for data-driven decision making in schools – eLearning Industry. Retrieved from https://elearningindustry.com/educational-data-analytics-technologies

27
Aug

Pre-Sabbatical InstructureCarn – Summer 2018

I was checking in on my timeline I presented in my sabbatical proposal and remembered that my FPG travel in July was part of my sabbatical. My plan for Summer 2018 included attending the annual Canvas conference, InstructureCarn, which was held in late July in Colorado. I used FPG funds for this conference travel. At the conference I made some connections with more schools that are using Canvas Data Portal that I can hopefully connect with later during my sabbatical. 

Carnival TentThe conference had a carnival theme and a ton of sessions on Canvas Data, so I had a nice lineup to choose from. Most of the session presenters were actual data scientists, so a lot of what they talked about was over my head – very technical. It will be nice to go back and watch a few of the sessions again once Instructure posts the recordings online and I know little more about the technical side. For instance, the first session I sat in was Concept-Based Data Analysis: A New Method for Organizing and Visualizing Data Using Course Design Principles. Fascinating stuff, but I had no idea how to get to where they were. The presentation explained that by combining sound pedagogical principles with new methods of data collection from Canvas, there’s a method for visualizing classroom data to evaluate the effectiveness of course material, highlight concepts that call for improvement, and present this data to students, faculty, and administrators in a holistic format. Yes, please!

The next session I attended made a lot more sense to me, a novice, and was geared more to what I imagine I could possible persuade our campus to set up. The presentation, Determining Student Activity in Canvas Data, showed how you can efficiently clean and use the data in Canvas Data to build a database and determine student activity and grades from just a few tables. The one thing I’m learning about all these great data projects is that it takes a team to develop them. They get buy-in from admin, IT, Student Services, Faculty and Data Scientist before they create anything. That could end up being a challenge for me.

Candied ApplesOverall, I attended 10 sessions that had something to do with Canvas Data or Analytics. Luckily for me Instructure had a lot of planned fun carnival activities built into the day and evening because my brain hurt after some of those sessions. But it was nice to unwind in the evening with colleagues and friends. We actually attended a carnival with all kinds of different street food, rides and games. I mean, who could pass up a table full of candied apples. We couldn’t!

I think Beth may have had too much sugar.

And yes, I did eat the whole thing. We even got little panda bears and all kinds of other swag.

All in all it was time well spent, both in the conference sessions and all the fun in between. I will say my biggest disappointment was a session I was looking forward to disappeared off the program and no longer existed. It was the perfect session for me: A Non-Programmers Guide to Using the Canvas Data Portal. Yes! Sign me up. Nope. Gone. 🙁  They enticed me with: “The Canvas Data Portal is a great tool, but can be intimidating for non-technical or non-programming professionals. In this session, I will go through my personal journey learning and utilizing the Canvas Data Portal as well as provide tutorials, tips, and strategies for non-technical or non-programming individuals so they can fully utilize the Canvas Data Portal in their Canvas Instance.” But then they didn’t show up. No “personal journey.” No “tutorials, tips, and strategies.” I should track them down.

 

26
Aug

Sabbatical 2018 Week 2: Big Data Modeling

I survived week 2 of my sabbatical. I spent a good portion of time learning about big data modeling. I learned a few things including how to identify the major components in semi-structured data from a weather station and how to create plots of weather station data. I’m not confident I really learned how to do this; however, I was able to follow directions and type in the correct commands to get the desired results.

VMVirtualBoxThe challenge is that we’re using this Oracle VM VirtualBox, and I’m not certain why. For instance, one of the first steps was to open a spreadsheet application in the terminal shell. All was fine until I got an error message when running command “oocalc”. No spreadsheet application for me. I checked the discussion forum and found others have had this same error, but all the suggested fixes didn’t work for me. I posted my problem and have not yet received any help. Now I understand why so few people complete MOOCs. You’re on your own.

Oh well. Screw the terminal. I just downloaded a LibreOffice spreadsheet application to my computer and loaded up the CSV file and everything worked fine. I did try to use Microsoft Excel at first, but the instructions didn’t match up.

Later in the week I had to go back to the dreaded VirtualBox to learn how to display the nested structure of a JSON file and to extract data from a JSON file. This time we were playing around with some Twitter data and everything was fine. My confidence was boosted although temporarily. I had some challenges in the terminal shell in the next lesson trying to view the dimensions and pixel values in a image. It didn’t work at all for me. So I rolled my eyes and sent a silent prayer that that knowledge would never be necessary. I’m starting to get a feel for how some of my students might feel when learning new concepts in Comp I and II. They’re probably praying that I never ask them to demonstrate certain skills ever. I feel your pain.

I ended the week with a few more mishaps in the VirtualBox. I’m really hoping the tool is not a standard tool for data analysis and something that’s related to how Coursera works. I’m getting a little tired of watching a video of the tool working great, but when I try it – FAIL! It’s really not good for my ego or my confidence. But I will persist.

sarcasticUp next I’ll be finishing up the first course: Intro to Big Data and moving on to Week 3 of 6 in the Big Data Modeling and Management Systems course. Can’t wait to use the VirtualBox!

I also need to set up a meeting with district Canvas support to discuss the Canvas Data Portal. They’re going to turn that right on once I ask.

13
Aug

Sabbatical 2018 Week 1: Getting Started with Big Data

Coursera: Big Data Specialization

Coursera: Big Data Specialization

Happy Sabbatical to me and Lisa Young. Today begins my journey into the world of Big Data. I’m starting by taking two Coursera Specializations on big data. A Coursera Specialization is a series of courses that helps you master a skill. I’m beginning with the Big Data Specialization by UC San Diego. This specialization includes 6 courses. Description: “Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data.”

I was glad to discover this specialization on Coursera because it’s exactly what I need for my sabbatical, and the best part is it only cost $50 a month. I’m anticipating I can finish in 3-4 months. The series is designed to be a part time endeavor; however, I have lots of time to devote to the courses. UC San Diego is an academic powerhouse, recognized as one of the top 10 public universities by U.S. News and World Report, so I’m pleased to be learning from this elite group of instructors. The San Diego Supercomputer Center (SDSC) at UC San Diego is a leader in data-intensive computing and cyberinfrastructure.

The second specialization I plan to take is the Data Scientist Specialization by Johns Hopkins University which includes 10 courses. Description: “Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you’ll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results.” I’m a bit apprehensive about this series, as they do recommend some programming experience (in any language). And they also suggest “a working knowledge of mathematics up to algebra.” Ugh! I’m not sure I have a working knowledge of mathematics. I guess we’ll see. I somehow managed four college degrees (AA, BA, MA, EDD) and only remember taking one math class (college Algebra) which I took way back in 1984. Lucky for me Coursera offers a course for people like me: Data Science Math Skills by Duke. It’s a 4 week course that is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. We’ll see how this goes. Wish me luck.

3
May

FEP 2018: Elected Areas – Professional Development & Research Projects

In addition to an assessment of these “3 REQUIRED AREAS” (RFP Section 3.5.3.1.) , “AT LEAST TWO ELECTED AREAS” (RFP Section 3.5.3.2.), and other “RELATED AREAS” (REP Section 3.5.3.3.)  may also be selected by the faculty member to review, in order to bring into better focus their full professional involvements at the college or within the District.  Examples include program coordination, research projects, department/division chair responsibilities, student activities-advising/mentoring, professional involvement in the community, professional growth, involvement/projects, professional interaction with colleagues, etc.

  • AT LEAST TWO ELECTED AREAS:
    • Professional Development &
    • Professional Interaction with Colleagues
  • RELATED AREAS: 

    • Involvement/Projects

I could easily write a post about my involvement in our MCLI Grant: Analytics for English Faculty Learning Community and our subsequent research study, Using Data to Improve Student Success in eCourses, but that would be too easy, and I’m not ready to reflect on that yet. So instead I’m going to reflect on my professional development and my professional interactions with colleagues in coordinating this year’s TYCA West conference at Glendale Community College.

This was the first time GCC has hosted the annual TYCA West conference that routinely rotates between Arizona, Utah, and Nevada. I bravely volunteered us while we were in Salt Lake City for the 2016 conference, so naturally, I would be in charge. This didn’t bother me, as I knew we had a great team here at GCC and we would have plenty of planning help. To toot my own horn, we pulled it off.

TYCA-West is the Two Year College English Association for the Western Region. TYCA-West functions under the umbrella of the parent organization, National TYCA. National TYCA is part of NCTE (National Council of Teachers of English). Within National TYCA there are seven regions. TYCA-West serves faculty in Utah, Idaho, Wyoming, Arizona, Nevada, and Hawaii.

I’ve been a member of the TYCA-West Executive Committee for eight years as the webmaster, which sounds way more impressive than it really is. I designed the site, which runs on WordPress, and then helped keep it up-to-date. After this last year, I passed the torch and am no longer part of the committee. That’s just one of many commitments I’ve given up after this year.

It was a great experience working with my colleagues to put this conference together. It was one of the biggest TYCA West conferences to date with over 150 participants. We had about 15 faculty from the department helping, and I was surprised that our Reading faculty, who are part of our department of 40, chipped in to help, presented and attended the conference. I’d never organized anything this big before, but my best decision was getting taskmaster, Beth Eyres, involved. “Chop, chop!” Truth be told, she really did all the work. Ha! At least the making sure it all got done part.

We started with a list of things that needed to be done. I was amazed at how long that list was. Then we asked for volunteers to pick just one task. When you have a department of 40, you can spread it out like that if people are willing to help. And willing they were. I was surprised by how into it people got. Ray Lira was my favorite. He and Rashmi designed and printed the program, and he was so excited about it. It turned out really good too.

These are the professional interactions with colleagues that I came to GCC for and they delivered for this project and every day since I got here. It’s great to be able to work with a team to accomplish something big.

The conference had a great theme and keynote speaker thanks to Shelley Rodrigo, GCC adjunct and Assistant Professor in the Department of English at the University of Arizona. She came up with the idea the same day we volunteered to host.

The theme for our 2017 conference was “The Measure of Tomorrow: Assessment through the Lens of Race, Diversity, & Inclusion. “Community colleges serve some of the most at-risk students.  Nearly half of all students enrolled in higher education in the United States are enrolled in two-year colleges. Nationally, 58% of two-year college students receive aid, while 72% apply. Demographically, two-year college students are widely diverse in age, race, ethnicity, and income-status (American Association of Community Colleges).

Race, gender and class shape the experience of all people. Therefore it is natural to agree that this should be considered when developing assessments in education, as well as the importance of infusing culturally relevant pedagogy into the academic curriculum. And in so doing, faculty today must consider alternative assessment methods that include strategies of assessment that could be put into practice to include, rather than exclude, students in order to serve more diverse learners.

Shelley also suggested that we invite Dr. Asao Inoue, Professor and Writing Center Director at the University of Washington, Tacoma to be our keynote. His provocative talk was interesting and created an opportunity for great dialogue and set the stage for a great conference.

The breakout sessions were great and the conference was well attended. We set out with a goal to make it the best TYCA West conference yet, and I think we succeeded. It was one of the largest, if not the largest in attendance, and we added in a few modern upgrades: online conference schedule viewable on mobile, a Tweet Wall, CFP closed on time with no extension needed, and the first annual TYCA West Pub Crawl Scavenger Hunt using Goosechase.

25
Apr

FEP 2018: Instructional Delivery & Design Thoughts

To complete an FEP each faculty member must engage in a self-examination of “THREE REQUIRED AREAS”:

  • TEACHING (OR OTHER PRIMARY DUTIES).  For example, instructional or service delivery, content expertise, classroom or program management, instruction/program design. This year I decided to focus on instructional delivery and design.

I’ve written previously about a redesign of my hybrid ENG102 course, so I’m going to continue that discussion here with a focus on instructional delivery and design. One of the many things I wanted to focus on this semester was better instruction for my hybrid students. The current instruction and design wasn’t bad, but I wanted to see if I could make changes to improve it. With this in mind, I decided to focus on feedback in grading, more one-to-one interactions, and more engaging in-class instruction.

In the past I’ve always graded student work in a digital format, mostly using a tool built into the publisher software I’ve used for 8 years, Connect Composition. Connect is great in that it makes it easy for the instructor to type feedback on the essay, and it saves the responses so if you have to say the same thing (think: Run-on sentence) over and over again on every student’s paper, you only have to type the R and the phrase just pops up, you select it, and you’re good to go. It saves a lot of time when grading. However, this semester I wanted to try some different technology tools, so I didn’t use Connect.

After trying to grade papers in Canvas one time, I gave up on that idea. Instead I decided to try grading using my Samsung Galaxy book. It’s a 2 in 1 PC that runs Windows and Office. It comes with an S pen and you can write right on the documents using Ink in Word. It was really easy to do and I quickly resorted back to my 1990’s self and began scribbling all over my students papers. I scribbled circles and boxes, arrows, lines and words. It was fun.

But I quickly realized that after several emails and texts asking what a particular scribble meant, that maybe this new (archaic) method of providing feedback was not as successful as I’d hoped. I mean the technology was great, but the practicality of it was not. And I have to give credit to my students who were very creative in their methods for asking for help. I got phone images of my scribbles, screenshots of them and even the scribbles written out using the letters they could recognize. “Dr. Cooper. What does frog mean?” Ha! Okay, okay, I can admit failure.

student conferencesWhat this failure transcended into was a bunch of one on one webinar conferences with me explaining all of my scribbles on the graded paper. If I got a message saying they didn’t understand something, I’d quickly send a Google Meet (Hangout) invite to the student and we’d go over it. I share my desktop, pull up their graded paper, and discuss. They loved it. So now I just set up that option after each paper is returned. I use Calendly to set up appointments. Students click the link to sign-up. The appointments get added directly to my Google calendar. Once I get an appointment, I edit the calendar event and add the Google Hangout and the student to the event. They get an invite, and when the time comes, we meet online.

This is an instructional strategy that has worked well. I still need to work on my scribbles, but students like the one on one interaction as we talk over their paper, and they can hear what I was thinking when I go over the marks on their papers. This is nothing revolutionary by any means, but it’s something I hope to continue. Although it might be tough when I’m teaching a full load (5 classes) in the future.

This strategy also helped with my goal to engage more with each student individually. I’m part of a MCLI Learning Grant this year with a group of other GCC ENG/RDG faculty who teach hybrid and online. Our project, Using Data to Improve Student Success in eCourses, involves sending personalized messages to students who fall into several categories: doing well, maintaining, improved, deteriorated, average maintaining, danger (red flag). After we send the messages, we take note of any changes in the students’ grade/behavior, and we’re surveying them to see how they felt about the messages. That might be a blog post soon.

I used the commenting feature in Canvas assignments to leave most of my messages. I usually use rubrics for grading assignments, and only occasionally will I throw in a “Good job” or “You need to redo this assignment.” My messages this semester were more personalized based on the category the student fell in. I wanted the student to feel as if I was talking just to him/her. I also used Remind to text my students. Each week I’d pick 3-4 students and send them a personal text. I’d text things like “Nice job on your last paper. You’re doing a great job in this class.” This was really easy because luckily all my students are doing well (C or better). Most of the texts for negative behaviors were for missing an assignment. “You didn’t submit your paper last night. Make sure you get that in right away. I’d hate for this to affect your grade. Let know if you need help.”

Lastly, I improved my in-class instruction by adding in more student interactions. We played Kahoot! games at the beginning of each Tuesday class session. The games covered the material in their online lessons. The students worked in teams early on to write a group argument paper on Net Neutrality, so we spent more time doing group activities, and last we shared more student work during class and talked about how the work was good or how it could be improved. With these in-class additions, we spent less time going over the online work, which in the past I felt was needed. Turns out I didn’t need to waste class time on reading directions for students.