How Much Knowledge Is Too Little? When a Lack of Knowledge Becomes a Barrier to Comprehension

2019 ◽  
Vol 30 (9) ◽  
pp. 1344-1351 ◽  
Author(s):  
Tenaha O’Reilly ◽  
Zuowei Wang ◽  
John Sabatini
Keyword(s):  
High School ◽  
High School Students ◽  
Natural Language Processing ◽  
Language Processing ◽  
Positive Relation ◽  
Specific Topic ◽  
School Students ◽  
Knowledge Test ◽  
Processing Techniques ◽  
The Relationship

Have you ever found it difficult to read something because you lack knowledge on the topic? We investigated this phenomenon with a sample of 3,534 high school students who took a background-knowledge test before working on a reading-comprehension test on the topic of ecology. Broken-line regression revealed a knowledge threshold: Below the threshold, the relationship between comprehension and knowledge was weak (β = 0.18), but above the threshold, a strong and positive relation emerged (β = 0.81). Further analyses indicated that certain topically relevant words (e.g., ecosystem, habitat) were more important to know than others when predicting the threshold, and these keywords could be identified using natural-language-processing techniques. Collectively, these results may help identify who is likely to have a problem comprehending information on a specific topic and, to some extent, what knowledge is likely required to comprehend information on that topic.

scholarly journals Lessons Learned from Teaching Machine Learning and Natural Language Processing to High School Students

2020 ◽  
Vol 34 (09) ◽  
pp. 13397-13403
Author(s):  
Narges Norouzi ◽  
Snigdha Chaturvedi ◽  
Matthew Rutledge
Keyword(s):  
Machine Learning ◽  
High School ◽  
High School Students ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Teaching Machine ◽  
Lessons Learned ◽  
School Students ◽  
Gender Discrepancies

This paper describes an experience in teaching Machine Learning (ML) and Natural Language Processing (NLP) to a group of high school students over an intense one-month period. In this work, we provide an outline of an AI course curriculum we designed for high school students and then evaluate its effectiveness by analyzing student's feedback and student outcomes. After closely observing students, evaluating their responses to our surveys, and analyzing their contribution to the course project, we identified some possible impediments in teaching AI to high school students and propose some measures to avoid them. These measures include employing a combination of objectivist and constructivist pedagogies, reviewing/introducing basic programming concepts at the beginning of the course, and addressing gender discrepancies throughout the course.

Maximizing ANLP Evaluation

2012 ◽  
pp. 438-456
Author(s):  
Adam Renner ◽  
Philip M. McCarthy ◽  
Chutima Boonthum-Denecke ◽  
Danielle S. McNamara
Keyword(s):  
High School ◽  
High School Students ◽  
Natural Language Processing ◽  
Language Processing ◽  
Learning Systems ◽  
School Students ◽  
Computational Approaches ◽  
Tutoring Systems ◽  
User Input ◽  
Controlled Natural Language

A continuing problem for ANLP (compared with NLP) is that language tends to be more natural in ANLP than that examined in more controlled natural language processing (NLP) studies. Specifically, ineffective or misleading feedback can result from faulty assessment of misspelled words. This chapter describes the Harmonizer system for addressing the problem of user input irregularities (e.g., typos). The Harmonizer is specifically designed for Intelligence Tutoring Systems (ITSs) that use NLP to provide assessment and feedback based on the typed input of the user. Our approach is to “harmonize” similar words to the same form in the benchmark, rather than correcting them to dictionary entries. This chapter describes the Harmonizer, and evaluates its performance using various computational approaches on unedited input from high school students in the context of an ITS (i.e., iSTART). Our results indicate that various metric approaches to NLP (such as word-overlap cohesion scores) are moderately affected when student errors are filtered by the Harmonizer. Given the prevalence of typing errors in the sample, the study substantiates the need to “clean” typed input in comparable NLP-based learning systems. The Harmonizer provides such ability and is easy to implement with light processing requirements.

Description Of Relationship Between Students Interests And Attitudes In Physical Subject In Indonesia

2019 ◽  
Vol 5 (3) ◽  
pp. 202
Author(s):  
Astalini Astalini ◽  
Darmaji Darmaji ◽  
Dwi Agus Kurniawan ◽  
Sumaryanti Sumaryanti ◽  
Rahmat Perdana ◽  
...  
Keyword(s):  
High School ◽  
High School Students ◽  
Descriptive Statistics ◽  
Student Interest ◽  
School Students ◽  
Analysis Techniques ◽  
High School Physics ◽  
Research Procedure ◽  
The Relationship ◽  
Good Research

The purpose of this study is to find out how attitudes and interests of students and analyze the relationship between attitudes and student interest in high school physics subjects in Jambi Province. This type of research is quantitative which uses survey research design as a research procedure. This study involved 463 high school students in Jambi Province. The instrument used was a questionnaire with data analysis techniques namely descriptive statistics and inferential statistics. The results of the dominant student attitude indicators discussed in this paper are attitude indicators towards good research in physics with a percentage of 58.5% with a total of 271 students. The results of indicators of dominant interest are indicators of learning attention with categories good a percentage of 74.3% with total 344 students. The results of the analysis of the relationship between attitudes and interests of students towards high school physics subjects in Jambi Province showed r value 0.725 and positive. Therefore it is said that the attitudes and interests of high school students in Indonesia in physics subjects are high.

THE RELATIONSHIP BETWEEN SMART PHONE USAGE AND SLEEP DISTURBANCES AND PSYCHOLOGICAL DISSTRESS AMONG STUDENTS

2017 ◽  
pp. 125-130
Author(s):  
Minh Tam Nguyen ◽  
Phuc Thanh Nhan Nguyen ◽  
Thi Thuy Hang Nguyen
Keyword(s):  
High School ◽  
High School Students ◽  
University Students ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Public Health Problem ◽  
Smartphone Addiction ◽  
Poor Sleep ◽  
School Students ◽  
The Relationship

The increasing use of smartphone among young people is creating negative effects and is an important public health problem in many countries. Smartphone abuse and addiction may cause physical and psychological disorders among users. However, the awarenes on this issue has been inadequate due to lacking of evidence. Objectives: To describe the current situation of smartphone using among students at highschools and universities in Hue city and to examine the relationship between smartphone using and sleep disturbances and psychological disstress among participants. Methods: A cross-sectional study with a randomly selected sample of 1,150 students at highschools and universities in Hue city. SAS-SV scale was used to evaluate phone addiction status, K10 scale was used for psychological distress assessment and PSQI scale was used to examine the sleep quality. Results: The proportion of students at highschools and universities having smartphones was 78.0%. The rate of smartphone addiction among high school students was 49.1% and that among university students was 43.7%. There was 57.3% of high school students had poor sleep quality, and that of university students was 51.6%. There was a statistically significant association between smartphone addiction and sleep disturbances and psychological disstress among participants (p <0.05). Conclusion: The prevalence of smartphone addiction among students at highschools and universities is alarming and is related to sleep disturbances and psychological disstress among participants. There is a strong call to develop intervention to help students to aware and manage the use of smartphone effectively.

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