[Grammar] Abstract - help

[imgaboy]

Hi there,

I have to create an abstract for my research. I have been finished a part of this.
Can somebody help me to check my abstract?

Here is my document:

During the literature review, we have realized that there is two type of research could find in papers. The first group use a huge log file from edX or Coursera which has been generated by big Universities like Stanford or MIT. These data have generated by ten or more thousand self-motivated students. On the other side, there is a second group which want to create a successful prediction model from Moodle. For this, they use a very poor data from Moodle or Moodle based forums. In our research, we have used a unique log-data which has been created by own system. During the logging process, the students were motivated by teacher and school. Our data’s parameters were same wide and deep as the data from edX and Coursera, but it has created in much shorter period than that. This log file gave us an opportunity to study clickstream data and user attitudes in short MOOC’s. In our paper, the main point was to create a classification model which could predict the engagement by using clickstream data form short MOOC course log data.

 

[tedmc]

Hi there,

I have to create an abstract for my research. I have been finished a part of this.
Can somebody help me to check my abstract?

Here is my document:

During the literature review, we [STRIKE]have[/STRIKE] realized that there[STRIKE] is[/STRIKE] are two types of research that could [STRIKE]find[/STRIKE] be found in papers (research papers?). The first group uses a huge log file from edX or Coursera which has been generated by big Universities like Stanford or MIT. These data[STRIKE] have[/STRIKE] has been generated by ten or more thousand self-motivated students. On the other side, there is a second group which want to create a successful prediction model from Moodle. For this, they use [STRIKE]a[/STRIKE] very poor data from Moodle or Moodle-based forums. In our research, we have used a unique log-data which has been created by own system. During the logging process, the students were motivated by the teacher and the school. Our data’s parameters were the same - wide and deep as the data from edX and Coursera, but it [STRIKE]has[/STRIKE] had been created in a much shorter period than that. This log file gave us an opportunity to study clickstream data and user attitudes in short MOOC’s. In our paper, the point was to create a classification model which could predict the engagement by using clickstream data form short MOOC course log data.

.