Using KidLogger for research study

Scientists around the world using KidLogger application to research on humans psychometric modeling using digital data traces which are produced by computer usage. The major challenges are to detect how some temporal activity metrics are correlated with certain Big Five personality metrics (FFM) that has been defined as 'openness to experience', conscientiousness, extraversion, agreeableness, and neuroticism (often represented by the acronyms OCEAN or CANOE). Also determining various effects on multitasking work in computer environment and its correlation with stress represents the big area of research. The negative influence of social media on a students mood as a distraction factor is also among the biggest findings by the researchers, which means that further investigation into social media usage should be made in future. In other hands measuring digital traces allows to find the influence of other factors into information workers such as amount of sleep, physiological or cognitive reasons, offsite motivation;
The scientific community also works to discover effective collection methods and better measure of information about the use of the computer applications by the user for later studying the patterns of user's behavior. Various industries are also highly interested in developing a measurement model for human factors decisions and privileged user behavior in critical information infrastructures that helps in computer forensics and security. In educational environment there was attempts to monitor computer traces to find gaps in learning processes to establish professional ethics for translators;

KidLogger application allows to collect various traces of user activity with a computer or mobile devices. The list of traces includes:

  • Start and end time of computer usage since Computer or Smartphone startup;
  • Programs usage time, switch time;
  • Window title activation time;
  • Input idle start, stop and duration time;
  • Web site usage, switch and activation time;
  • Mouse movements and clicks;
  • Keyboard typing events, with active application or web site name;
  • Communication data: Skype in / Out messages;
  • Web Browser plugin with in-depth web page activity traces: scroll, click, hover navigation, UI responce wait time;
  • Eye tracking data (with IR camera, Windows 10 only);
  • Periodic display screenshot capture;
  • Periodic web-camera photo capture;
  • Microphone sound recording to detect voice communication activity;

KidLogger allows to produce data in CSV, JSON, HTML formats with millisecond-precision format;

Target Group studies with KidLogger is possible with On-Premise KidLogger Cloud that allows to collect and analyze data across class, school or university scope. Please contact us for more information.

How to setup KidLogger for research

Install KidLogger Application, open KidLogger.net and Options (Kidlogger.net). Define Format options. Define millisecond time format and granularity vs aggregation.

By default KidLogger application does not require to connect with cloud service and it possible to conduct monitoring and store data locally on the computer.

How to collect data from CSV or JSON file

KidLogger allows to output collected data into CSV or JSON file for later processing. The data includes date and time of event, type, name, title, duration and attribute.

 

Mouse events, 'mouse' tag:
mouse,13:24:00:526,notepad, Move ,1437:945
mouse,13:24:00:558,notepad, Move ,1354:849
mouse,13:24:00:590,notepad, Move ,1313:806
mouse,13:24:00:621,notepad, Move ,1295:776
mouse,13:24:00:646,notepad, Move ,1278:738

mouse,11:08:53:474,notepad, Scroll ,689:728
mouse,11:16:23:698,notepad, Click ,144:30

where 'notepad' is currently active process name.

Keyboards events, 'keystroke' tag:

keystroke,13:19:34:7,notepad,t
keystroke,13:19:34:91,notepad,y
keystroke,13:19:34:459,notepad,p
keystroke,13:19:34:932,notepad,i
keystroke,13:19:34:940,notepad,n
keystroke,13:19:34:992,notepad,g

Current UI application selection, 'app' tag:

app,13:25:47:854,notepad,Untitled - Notepad

kidlogger is currently the application currently selected by user with 'Untitled - Notepad' window caption (title).

Current Web site URL selection, 'url' tag:

url,11:16:23:625,0,https://mail.google.com/mail/u/0/#inbox,Incomming (96) - test@gmail.com - Gmail - Google Chrome

Other tags: system, folder, mp3, idle, jpg, chat

 

On-Premise KidLogger Cloud

Allows to collect data into a central location across multiple devices located over the School or organization departments;

Combines data for a single personality across multiple devices like phones and computers and integrate them into a single journal record. This simplifies to perform multi-device context studies.

Data export: SQL tables with traces data.

Open-Source monitoring tool

We are always open for collaboration with educational organizations and ready to provide the latest source code of KidLogger applications, Cloud Server and support research with our experimental custom features.

 

List of references

This list will help you to better define the scope and achievements
of past researches. The list of researches and studies conducted in the field:

 

Detecting Multitasking Work and Negative Routines from Computer Logs

https://link.springer.com/chapter/10.1007/978-3-319-40397-7_52

 

Strictly by the Facebook: Unobtrusive Method for Differentiating Users

https://dl.acm.org/citation.cfm?id=2698996

 

Digital footprints: predicting personality from temporal patterns of technology use

https://dl.acm.org/citation.cfm?id=3123139

 

Stress and multitasking in everyday college life: an empirical study of online activity

https://dl.acm.org/citation.cfm?id=2557361

 

Sleep Debt in Student Life: Online Attention Focus, Facebook, and Mood

https://dl.acm.org/citation.cfm?id=2858437

 

Development of an Application for Mobile Devices to Record Learner Interactions with Web-Based Learning Objects

https://ieeexplore.ieee.org/abstract/document/6268085

 

 

Collecte, traitement et analyse de traces pour identifier la circulation de pratiques numériques des lycéens

https://hal.archives-ouvertes.fr/hal-01460633/

 

Workstation Analytics in Distributed Warfighting Experimentation

http://www.dodccrp.org/events/19th_iccrts_2014/post_conference/papers/060.pdf

 

More friends, more interactions? The association between network size and interactions on Facebook

https://journals.uic.edu/ojs/index.php/fm/article/view/8195

 

"LA TRADUCCIÓN DE FRASEOLOGISMOS EN EL AULA DE TRADUCCIÓN GENERAL "

Gisela Marcelo Wirtnizer José Jorge Amigo Extremera

http://www.diva-portal.org/smash/record.jsf?pid=diva2:942582

Exploring mobile device usage patterns by using the FANN neural network library