Democratising Goal Setting: Possibilities and Pitfalls of Online Deliberation and Big Data Methods

A weighty argument in favor of including the new educational area «Big Data» in the practice of professional training of the future economist is the competence in the field of building adequate predictive models, which is in demand in the modern labor market. Indeed, any leader is interested in improving the quality of the decisions made. This interest increases in conditions of sanctions pressure and post-pandemic restrictions, in difficult socio-economic conditions, when most of the resources are limited, the previously identified cause-and-effect relationships lose their relevance and the responsibility for decisions is significantly increased. Features of the implementation of the technological approach to disclosing the content of the new educational area «Big Data» in the system of professional training of the future economist is presented in this article as follows: firstly, in the form of a system of micro-goals at the basic level, and secondly, in the form of a system of micro-goals at an advanced level. Thus, within the framework of the technological goal-setting of the content of the new educational field, the principle of variability of the professional training of the future economist is implemented. Substantively presented in the article micro-goals cover various issues of using quantitative methods, mathematical and computational modeling. In addition, the formulations of micro-goals include requirements for the development of new tools that support big data analysis. Note that the implementation of technological goal-setting is necessary to strengthen the applied orientation of the training of a future economist, allows us to make a methodological emphasis on applied problems of socio-economic topics, the methods of solving which are in demand in future professional activities. The material of the article can be useful to teachers of the higher school of economics, as well as to anyone interested in modern methodological approaches to structuring educational content and achievements in the field of big data.

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Find Out About 'Big Data' to Track Outcomes

ASHA Leader ◽

10.1044/leader.an5.18022013.59 ◽

2013 ◽

Vol 18 (2) ◽

pp. 59-59

Keyword(s):

Big Data

Find Out About 'Big Data' to Track Outcomes

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U.S., Canada Collaborate on Big Data in ASD Research

ASHA Leader ◽

10.1044/leader.nib4.20122015.16 ◽

2015 ◽

Vol 20 (12) ◽

pp. 16-16

Keyword(s):

Big Data

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Undesirable Effects of Goal Setting on Perceived Fairness, Commitment, and Unethical Behavior

Zeitschrift für Arbeits- und Organisationspsychologie A&O ◽

10.1026/0932-4089/a000267 ◽

2018 ◽

Vol 62 (2) ◽

pp. 97-107 ◽

Cited By ~ 2

Author(s):

Nina Keith

Keyword(s):

Goal Setting ◽

Unethical Behavior ◽

The United States ◽

Goal Commitment ◽

Management Technique ◽

Long Term Effects ◽

Perceived Fairness ◽

Negative Effects ◽

Positive Effects ◽

And Performance

Abstract. The positive effects of goal setting on motivation and performance are among the most established findings of industrial–organizational psychology. Accordingly, goal setting is a common management technique. Lately, however, potential negative effects of goal-setting, for example, on unethical behavior, are increasingly being discussed. This research replicates and extends a laboratory experiment conducted in the United States. In one of three goal conditions (do-your-best goals, consistently high goals, increasingly high goals), 101 participants worked on a search task in five rounds. Half of them (transparency yes/no) were informed at the outset about goal development. We did not find the expected effects on unethical behavior but medium-to-large effects on subjective variables: Perceived fairness of goals and goal commitment were least favorable in the increasing-goal condition, particularly in later goal rounds. Results indicate that when designing goal-setting interventions, organizations may consider potential undesirable long-term effects.

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Correlating Personality and Actual Phone Usage

Journal of Individual Differences ◽

10.1027/1614-0001/a000139 ◽

2014 ◽

Vol 35 (3) ◽

pp. 158-165 ◽

Cited By ~ 38

Author(s):

Christian Montag ◽

Konrad Błaszkiewicz ◽

Bernd Lachmann ◽

Ionut Andone ◽

Rayna Sariyska ◽

...

Keyword(s):

Big Data ◽

Social Network ◽

Mobile Phone ◽

Mobile Phones ◽

Self Report ◽

Psychological Variables ◽

New Approach ◽

Report Data ◽

Self Report Data ◽

Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

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“Big Data in Psychology: Methods and Applications”

Zeitschrift für Psychologie ◽

10.1027/2151-2604/a000295 ◽

2017 ◽

Vol 225 (3) ◽

pp. 287-288

Keyword(s):

Big Data

An associated conference will take place at ZPID – Leibniz Institute for Psychology Information in Trier, Germany, on June 7–9, 2018. For further details, see: http://bigdata2018.leibniz-psychology.org

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