Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Reliability and Validity01:29

Reliability and Validity

13.3K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
13.3K
Surveys02:16

Surveys

16.1K
Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
16.1K
Classification of Systems-II01:31

Classification of Systems-II

253
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
253
Self-Evaluation Maintenance Model01:29

Self-Evaluation Maintenance Model

18
The Self-Evaluation Maintenance (SEM) model offers a psychological framework to understand how individuals’ self-esteem is influenced by the achievements of others, particularly those with whom they share close personal bonds. The SEM model operates when personal rather than social identity guides individuals. Central to this model is the notion that individuals have an inherent desire to preserve a favorable self-image, which is continuously shaped by interpersonal comparisons and...
18
Classification of Systems-I01:26

Classification of Systems-I

348
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
348
Self-Evaluation: Self-Enhancement and Self-Verification03:00

Self-Evaluation: Self-Enhancement and Self-Verification

5.5K
Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...
5.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Impact of a Prototype Combining Recommender Functionality With Structured Documentation on Operator Performance in Calls to Medical Communication Centers: Quasi-Experimental Feasibility Study.

JMIR formative research·2026
Same author

Decoding Global Palates: Unveiling Cross-Cultural Flavor Preferences Through Online Recipes.

Foods (Basel, Switzerland)·2025
Same author

Supporting healthier food choices through AI-tailored advice: A research agenda.

PEC innovation·2025
Same author

Healthiness and environmental impact of dinner recipes vary widely across developed countries.

Nature food·2023
Same author

Nudging Healthy Choices in Food Search Through Visual Attractiveness.

Frontiers in artificial intelligence·2021
Same author

Using Natural Language Processing and Artificial Intelligence to Explore the Nutrition and Sustainability of Recipes and Food.

Frontiers in artificial intelligence·2021

Related Experiment Video

Updated: Oct 3, 2025

Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students
12:51

Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students

Published on: June 16, 2018

7.6K

Developing and Evaluating a University Recommender System.

Mehdi Elahi1, Alain Starke1,2, Nabil El Ioini3

  • 1Behavioral Data Analytics & Recommender Systems Research Group (DARS), Department of Information Science & Media Studies, University of Bergen, Bergen, Norway.

Frontiers in Artificial Intelligence
|February 21, 2022
PubMed
Summary

Finding the right university is hard. This study created a personalized university recommender system that uses user preferences to generate tailored rankings, outperforming traditional global rankings.

Keywords:
educationoffline evaluationrecommender systemsuniversityusabilityuser study

More Related Videos

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.3K
A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

4.0K

Related Experiment Videos

Last Updated: Oct 3, 2025

Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students
12:51

Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students

Published on: June 16, 2018

7.6K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.3K
A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

4.0K

Area of Science:

  • Educational Technology
  • Computer Science
  • Information Science

Background:

  • Global university rankings are widely used but often fail to meet individual student needs due to a lack of personalization.
  • Students have diverse preferences, including prestige and location, which are not addressed by generic ranking systems.

Purpose of the Study:

  • To develop and evaluate a personalized university recommender system for higher education.
  • To compare the effectiveness of different recommendation algorithms in generating tailored university rankings.

Main Methods:

  • Offline evaluation of recommender system algorithms using a rating dataset to assess predictive accuracy.
  • Online evaluation of three selected algorithms (SVD, KNN) using user feedback on metrics like accuracy, diversity, personalization, satisfaction, and novelty.

Main Results:

  • Singular Value Decomposition (SVD) algorithm demonstrated high accuracy and perceived personalization.
  • K-Nearest Neighbors (KNN) algorithm showed superior performance in terms of recommendation novelty.
  • Analysis of preferred university features among users was also conducted.

Conclusions:

  • Personalized recommender systems offer a more effective alternative to global rankings for university selection.
  • Different algorithms cater to distinct user preferences, with SVD excelling in accuracy and KNN in novelty.
  • The study provides insights into user preferences for university selection, informing future recommender system development.