scholarly journals Criminal Intelligence Activity and Criminology: A New Empirical Field for Crime Research

2021 ◽  
Author(s):  
Grigoriy Alexandrovich Maystrenko ◽  
Aleksey Dmitrievich Denisov
Keyword(s):  
Criminal Intelligence ◽  
Intelligence Activity ◽  
Empirical Field

scholarly journals Interdisciplinary Links in the Theory of Criminal Intelligence Activity

2021 ◽  
Author(s):  
Yaroslav Grigoryevich Ishchuk ◽  
Alexander Ivanovich Popov ◽  
Olga Alexandrovna Zygmunt
Keyword(s):  
Criminal Intelligence ◽  
Intelligence Activity

scholarly journals Providing a foundation for interpretable autonomous agents through elicitation and modeling of criminal investigation pathways

2020 ◽  
Vol 64 (1) ◽  
pp. 239-243
Author(s):  
Sam Hepenstal ◽  
Leishi Zhang ◽  
Neesha Kodogoda ◽  
B.L. William Wong
Keyword(s):  
Artificial Intelligence ◽  
Task Analysis ◽  
Autonomous Agents ◽  
Cognitive Task ◽  
Cognitive Task Analysis ◽  
Criminal Investigation ◽  
Event Tree ◽  
Analysis Method ◽  
Ethical Concerns ◽  
Criminal Intelligence

Criminal investigations are guided by repetitive and time-consuming information retrieval tasks, often with high risk and high consequence. If Artificial intelligence (AI) systems can automate lines of inquiry, it could reduce the burden on analysts and allow them to focus their efforts on analysis. However, there is a critical need for algorithmic transparency to address ethical concerns. In this paper, we use data gathered from Cognitive Task Analysis (CTA) interviews of criminal intelligence analysts and perform a novel analysis method to elicit question networks. We show how these networks form an event tree, where events are consolidated by capturing analyst intentions. The event tree is simplified with a Dynamic Chain Event Graph (DCEG) that provides a foundation for transparent autonomous investigations.

scholarly journals The Effect of Interactive Multiple Intelligences Activities Flip Module: Its Effects on Students’ Multiple Intelligences

2019 ◽  
Vol 8 (11) ◽  
pp. 342-348
Keyword(s):  
Multiple Intelligences ◽  
Test Analysis ◽  
Pedagogical Tool ◽  
Intra Class Correlation ◽  
Treatment Groups ◽  
Computer Based Learning ◽  
Intelligence Activity ◽  
Computer Based ◽  
High Degree ◽  
Intra Class Correlation Coefficient

This study aims to test an interactive pedagogical tool using a computer-based learning approach. The purpose of building Multiple Intelligences Activities Flip Module is to increase students’ potentials through their multiple intelligences. The true-experimental study design is used and the samples are randomly selected as control and treatment groups. Pre and post tests are used to measure the effectiveness of this interactive flip module in relations to multiple intelligences significant differences. The findings of the study reveal that the interactive Multiple Intelligences Activity flip module has a high degree of reliability whereby the average measure for Intra-class Correlation Coefficient is .771 with a 95% confidence interval from .520 to .931 (F(9,486)= 4.644, p<.000). Based on MANCOVA test analysis, the researchers have rejected the null hypothesis. The study has demonstrated that the Multiple Intelligence Activity flip module has increased the scores of multiple intelligences tests for treatment groups.

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