Soft Modeling and Special Education

This article briefly describes soft modeling with partial least squares (PLS) in a non-technical manner. Soft modeling with PLS was developed by Herman Wold (1985) for model building and evaluation in situations with high complexity but without well-articulated theories. Because many believe that this is the situation in education, we believe that soft modeling with PLS is a useful tool for educational research

Quantitative and Qualitative Analysis of the myGVSU (Climate Study) Survey

The myGVSU survey was administered in February 2011 to all GVSU faculty, staff, and students, of which over 7500 individuals participated. The survey contained 106 questions which translated into over 1000 unique variables since some questions had multiple parts; further, approximately 25 questions were open-ended and over 25,000 written comments were provided by respondents. The combination of quantitative and qualitative data provides a rich snapshot of how respondents felt about the overall climate of the university at the time of the survey’s administration

myGVSU Survey: Student Perceptions of the Most Recent University Climate – Understanding the Changing Student

The myGVSU Survey (4th climate study at GVSU) was administered in February 2011. This presentation will share select and early findings of student perceptions from the survey. Because students’ perceptions can influence how they learn and approach their overall university experience, faculty participants will reflect on how these findings might impact their teaching and discuss ensuing teaching strategies. Discussion points will be recorded and available electronically to participants by the end of start-up week

Increasing Statistical Literacy by Exploiting Lexical Ambiguity of Technical Terms

Instructional inattention to language poses a barrier for students in entry-level science courses, in part because students may perceive a subject as difficult solely based on the lack of understanding of the vocabulary. In addition, the technical use of terms that have different everyday meanings may cause students to misinterpret statements made by instructors, leading to an incomplete or incorrect understanding of the domain. Terms that have different technical and everyday meanings are said to have lexical ambiguity and statistics, as a discipline, has many lexically ambiguous terms. This paper presents a cyclic process for designing activities to address lexical ambiguity in statistics. In addition, it describes three short activities aimed to have high impact on student learning associated with two different lexically ambiguous words or word pairs in statistics. Preliminary student-level data are used to assess the efficacy of the activities, and future directions for development of activities and research about lexical ambiguity in statistics in particular and STEM in general are discussed

Zebra vs. Hats: Exploiting the Lexical Ambiguity of the Word Random

Words that are part of everyday English and used differently in a technical domain possess lexical ambiguity. Because people connect what they hear to what they already know, the use of a common English word in statistics may encourage students to incorporate the statistical usage as a new facet of the word they had learned previously. The use of words with lexical ambiguity, therefore, may encourage students to make incorrect associations between words they know and words that sound similar but have specific meanings in statistics that are different from the common usage definitions. One word integral to the understanding of statistics that has been shown to have lexical ambiguity for undergraduate students is random. Researchers in other fields suggest that in order to help students learn vocabulary instructors should exploit the lexical ambiguity of the words. Our poster will show the results of a study that is part sequence of studies designed to understand the effects of and develop techniques for exploiting lexical ambiguities of random in the statistics classroom and will include class activities and results instructors might obtain from the use of such activities

Communication in Statistics: Consideration of Lexical Ambiguity or I do not think this word means what you think it mean

People connect what they hear to what they have heard and experienced in the past, so if a commonly used English word is used differently by a technical domain, like statistics, a statistical novice might misunderstand the meaning of the communication. These domain-specific words that are similar to colloquial English words but have different meanings in statistics are said to have lexical ambiguity. The session presenter has been actively researching the role that language, and specifically ambiguous words, plays in the teaching and learning of introductory statistics and in this session will present findings that have the potential improve communication between consultants and their clients. In particular, research results with respect to the words random, normal, average, and association will be discussed and suggestions will be made to improve communication with clients by exploiting the ambiguities of the target words

Statistical consulting courses for undergraduates : fortune or folly?

This article presents an overview of three undergraduate-level statistical consulting courses being taught at institutions of different size (small, medium, and large). Topics that will be discussed include the evolution of these courses, thoughts on what makes such courses successful, potential pitfalls to watch for, the necessary minimal skills students should have to be successful in the courses, and thoughts on where these courses should appear in a statistics curriculum. This paper will provide an overview of the similarities and differences in the way applied consulting courses are presented within the three undergraduate programs

Lexical Ambiguity in Statistics: How students use and define the words: association, average, confidence, random and spread

reserved. This text may be freely shared among individuals, but it may not be republished in any medium without express written consent from the authors and advance notification of the editor. Key Words: Statistics education, Lexical ambiguity, Language, Word usage. Language plays a crucial role in the classroom. The use of specialized language in a domain can cause a subject to seem more difficult to students than it actually is. When words that are part of everyday English are used differently in a domain, these words are said to have lexical ambiguity. Studies in other fields, such as mathematics and chemistry education, suggest that in order to help students learn vocabulary instructors should exploit the lexical ambiguity of the words. The study presented here is the second in a sequence of studies designed to understand the effects of and develop techniques for exploiting lexical ambiguities in statistics classrooms. In particular, this paper looks at five statistical terms and the meanings of these terms most commonly expressed by students at the end of an undergraduate statistics course. 1