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Decreasing Student Procrastination Through E-mail and Multimedia Tools in Online Courses (OTC14)


Hello everyone. My name is doctor B E T H U N E. Joining me is doctor brown son. On slide. Before we begin talking about the details of our study on student pro crastination allow me to share with you other research. If you are watching this presentation you teach online or have some experience teaching. At times all I want is — not clear. Students must fill fulfill weekly assignments. According to O Z E R several students admit procrastinating. On slide. We all have procrastinated at some point in our lives, correct? I know I have. What is procrastination? Unable to complete a task in a timely manner. Two types. Active and passive. On slide. Interesting thing is they usually get their work submitted on time. I met someone in college that was like this. She enjoyed the rush it gave her to complete a 20 page paper the night before it was due. Passive procrastinate or on the other hand weights hand waits until the last minute. I’m sure we can all relate to this one. I’d like to bring to your attention attrition and attempt to tie in procrastination in one of the main factors. Think of for a brief moment why online colleges and universities are facing large attrition rates. Students are dropping out. Reasons are my financial aid didn’t get approved. I’m the only one working and I can’t work and take care of my family or I just need surgery and have to take a few months off. Lack of motivation and inadequate preparation. It is a big eye opener with first class and see how demanding it can be. Online can be more time consuming. Strategies of ideas to increase retention — determine if student need extra guidance throughout the term. Instruction at focus should be on inviting presence with virtual open door policy. Ask questions so they can adjust to expectations. Instructor student interaction may help alleviate any worries or stress the student is feeling. We were really concerned about the lack of on time submissions in introduction courses in college we teach. Strategy was proven unsuccessful. Student feels they are falling behind or receive below par grade, they give up. It is up to us to build them back up and encourage them the whole way through. Late or non submissions would be dropped from the course. We have to devise plan via e-mail and animation video. This is a way to keep students more accountable for being late with assignments. On slide. The intervention for this study were four animation videos were embedded and links sent to students. We were teaching introduction courses simultaneously. Experimental group there were total of 203 university online students. On slide. Gender wasn’t taken into account. Some students that were included in the study initially weren’t present at the end of the study. Some courses On slide. Each Tuesday V O K I was posted as announcements to introduce discussion and announcement for online students. This is a screen shot of video we posted. Emphasis on stating positive factors from discussion forums and written assignments from the previous week. On slide. If you would like the play the video you can see the link in the chat box on the left. Second V O K I was posted each Thursday as reminder for students to put initial discussion. There is a link in the chat box if you would like to click on it and view the video. Each Friday we devise V O K I. On slide. Final V O K I was placed in the announcement section. Encouraging reminder for students. On slide. There is a link in the chat box where you can click to view the video. Now doctor brown son will start sharing analysis of research. SPEAKER: Thank you. I just want to emphasize — we basically used tables and examined the results and improvements. That is our main emphasis is how much the students improved in the overall on time discussion posting. Our course is an entry point course and online university. One problem is high attrition rate for the first three weeks. We had written assignments for weeks one, 2 and 4. One decision cushion per week for discussions 1, 2, 4 and 5 and two discussions for week 3. We categorize the results in the tables under three categories. Discussion or written assignments posted on time; post ed late after the deadline and discussion was Thursday each week for the initial week and Monday. On slide. Higher percentage of students in the experimental group who moved to higher numbers of on time percentages. Basically about the same number of students or same percentage completed both the experimental and control groups. We had two experimental groups each as well as two control groups. In the control group the multi media intervention was minimal. The announcements were the standard announcements for the entry point course. We didn’t attempt to do any additional treatments in the experimental course. Again we posted V O K Is on Monday, Thursday Friday and the following Tuesday. What we did notice was the experimental groups there was gradual increase for on time posting of discussion threads. Interactive treatment On slide. One reason we can’t say for sure why we didn’t use sophisticated stat instruments and we didn’t contact the students directly. This is a bar graph about the control group percentage of students with on time discussion postings. We have control groups one through four. Coded by colors from week one to week five and week three are two different versions of blue. If you look carefully with the control group on time discussion postings they started off very high for control group one at 85 percent and declined by 7 percent — by week five. For control group 2 — on slide. Several factors occurred that may have influenced the on time postings. We have at least a ten percent or higher percent of students who don’t show up or drop the first week. Other I issues such as financial aid issues and other reasons . For control group 3 started out with 75 percent and final result of 93 percent and 100 percent in week 4. That is our outlier group. Whether you had treatment or not, there were superb results. In control group 4 slight increase from 72 percent on time in week one to 73 percent in week 5 which is a one percent increase. When you look at the experimental groups again it is in the same format experimental groups one for class one to class four. We had some fairly ^ descent ^ decent results. We totalled students each week and hand counted students that posted late or did not post at all. Usually did not post at all disappears by third week. If they don’t have 70 percent they are automatically dropped from the course. Experimental group increase from 85 percent to 86 percent to online discussion posts over 30 percent. There was a slight increase in experimental class 2, 76 percent in week one and 77 percent by week five or one percent increase. We also had for experimental group 3, 59 percent of the students posted on time for week one and by week 5 it was 80 percent with high of 95 in week two. It was over 20 percent that we noticed for the increase of on time discussion postings. Finally with experimental group 4 expanded from 75 to 79 percent or 4 percent. There are wide variations of these results. With your treatment you have to alter it. Perhaps V O K I is one way but numerous other ways. We start off with experimental group. Divided into experimental courses one, two, three and four. Green bar is week one assignment. Brown bar is week two and the blue bar is week four. It stayed about the same in experson /*R per perimental group one. 3 percent increase in week four with experimental group 2 there was increase going from 60 percent to 82 percent or 14 percent for online postings. Several factors may have come into play. One is higher drop rate. Students who stayed in the course had higher skills. The other one students got used to the assignments. You have to remember for many of these students our entry point course was the first one they would be taking for the university. For experimental course 3 there was week one on time posting of 55 percent and a week 4 on time posting of 75 percent which is fairly significant. Then of course you have group 4 which had about again almost 55 percent and shot up to 90 percent. There were other factors we did. We had samples and encouraged the students and had feed back. The whole idea that we had by using the V O K Is was to gradually encourage the students to move forward and post on time. Our main emphasis was to encourage students who weren’t doing well to do better. Reverse psychology. This is fascinating. There was significant results in three out of the four control groups as well for on time written assignments. Perhaps there is a self motivation or the V O K Is but we noticed more of an impact with the discussion threads. For control course one there was about 78 percent on time for week one and it stayed the same through week 4 with a bump of about 80 percent in week two. For control course two the results for week one showed about 64 percent on time in week one and 82 percent for week 2 which was a very major in crease. Finally, for the control group 3 course it went the opposite way which was interesting. I think it seems to be both the control group 3 and experimental group 3 were outlier courses with unusual stats that don’t match the rest. Week one was 70 percent and dropped down to 50 percent or dropped to 20 percent by week 4. Finally control course 4 stayed about the same. It was about 86 percent on time increase for week one and 88 for week four. Attrition retention the way we did this was that university what happens is you have a large number of students unfortunately for any online university that drop or have financial aid or other issues. What we really looked at were the students who stayed from week 3 to week 5. If you examine it again we have experimental courses one through four. Week two started out with 22 students. By week 3 there were 15 students total. What had happened is we lost 7 students but the majority of the students who did stay completed the course. The same with experimental group 2. We started off with 25 students and ended up with 17 or loss of 8. We only had — then we unfortunately experimental course two, two additional students dropped between weeks 3 and 5. Experimental group 3 — group 4 had 29 and 24 by week 3 and 19 by week five. If you look at the control group, this is where it is quite fascinating with the results. There was higher on time increase for discussion threads and equal in creation for written assignments but attrition rate for control group was much lower. In week one for control course one we started at 20 and ended at 18 so only two students lost. Online you don’t get to choose your students. There are different dynamics involved. These courses were at the end of the year in 2012. One was November December. Another was late November over winter break and went into early January. Control course 2 had 22 students in the beginning in week one. 21 in week 3 and by week 5 there were 16 but only lost 6 students. There were fewer students. The attrition rate for the control rate was much lower than for the experimental group. That was something we had to research further. Control course 3 started out with 23 students. Week one was 21 and ended up with week five 14 which was typical of experimental groups. Group 4 was 29 and went to 18 and 15. Control groups 1 and 2 had higher rates of retention. Our whole idea is that we were using the V O K Is a motivational tool. We were trying to find a different way to encourage students to stay in the class. In experimental course one, there were 24 students in week one and 15 at the end of the course. As I mentioned earlier students that have below 70 are automatically dropped. In addition 10 to 15 percent of the students usually leave the course before the end of week one. By week 5, 14 of the original 15 students who entered the course completed the class which that part is really important. After week 3 these are the true students in the course. We were able to get 93 percent of them. Overall retention rate was 63 percent. With experimental group 2 which was October 2013 start there were 29 students 6 mail, 23 female and by week 5, 16 completed. Total attrition rate was still 52 percent which is common for online. We are trying to reduce that by experimenting with different treatments. If you look at attrition rate for November to January course online submissions were similar — on slide. If you look at it overall the attrition rate for the control group was higher in two out of four classes compared to the experimental group. Overall completion rate was 53 percent. This includes students who dropped. While we don’t have perfect statistics we are hoping to replicate the study and perhaps have a student satisfaction survey afterwards to see more in depth if our study works. Completion rate for experimental group indicated a strong course completion rate. 29 students enrolled but 19 students in week 5 and 17 out of 19 completed the course with a final completion rate of 89 percent. Again to be honest the attrition rate was 59 percent and that is something we are seeking to improve. Examining control group one it was 89 percent from week 5 and 93 percent completed from experimental group one. The true statistics also is the control group had a hay higher overall retention rate. Control group 2 — on slide. There isn’t complete consistency for online postings due to attrition rate but what we hope to achieve and did achieve is hopefully at the end we did move the students forward. Forming positive reinforcement is our main emphasis. To push the student through the degree program and keep them /PHOETty motivated. You want to make sure your students are moving ahead. Doctor B E T H U N E will continue with the remainder of our presentation. SPEAKER: Thank you. It is clear that — not clear. There could be several other factors in procrastination. One student reported in class that she intended to be late with her discussion post due to ridge it’s rigid work schedule. Student was stuck in her ways and found it acceptable to turn in late work. From researchers opinion this is not main priority which is the case for some online students. /PHA Majority students have full time job. Some manage time and school and job and they want to take care of the children. There are other factors to consider in regards to pro crastinate and submit assignments past the due date. Lack of self regulation skills. This means they delay the completion of assignments because they feel compelled — on slide. Students that show online show less prepared — on slide. Expectations are far less than what is true of online environment. Courses are shorter than semester long. On slide. Online education as well structured environment — they feel they aren’t being monitored and without face-to-face interaction with the instructor they need to be held more accountable. On slide. Given encouragement and remindersof due dates

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