Lauer & Asher: Quantitative Descriptive Studies
Quantitative Descriptive research goes beyond case studies and isolates the most important variables and then attempts to quantify these. There are no control groups or treatments.
These studies need a larger subject group than ethnographies. Variable selection (choosing most important variables to quantify) is the most important part of this research. Alternative hypotheses are also used . Researchers look at the most important variables and find significance and how variables interact. Quantitative Descriptive Studies help to build theories, but they are usually inadequate to claim cause and effect relationships.
Study #1 A description of the composing process of freshmen
Study #2 Writing in a non academic setting
Study #3 Measuring growth in English
Farber: Popularizing Nanoscience
This research looked at how Nanoscience is discussed in popular media. Its Hypothesis and its findings showed that articles about nanoscience were socially adapted and used and that the articles created “personas” of the field.
Research Question: How has the field of Nanoscience been represented in the media from 1986 to 1999?
Subject Selection: Articles were selected by a search in a multi university database of articles and magazines.
Data Collection: The researcher looked for mentions of “nanoscience” and several other key categories in the field.
Data Analysis: The researcher looked at each articles discussion using the discursive categories of Theme, Rheme, Topic, and Representation
Golen: A Factor Analysis of Barriers to Effective Listening
This article found that there were 6 major barriers to effective listening. Age didn’t matter, but gender changed the impact of two of these barriers.
Research Question: What barriers do students perceive as most frequent? What are the listening barrier factors among students? How do these barriers differ among demographics?
Subject Selection: All subjects came from a large business lecture class after a lecture about overcoming listening barriers. This class broke into 33 sections. 10 of these sections were randomly selected for further study.
Data Collection: The barriers were obtained by finding the most common barriers as evidenced through a literature review, then edited through a pilot study and with professor’s and student’s suggestions. Next, the students’ age, major, and sex were measured across each barrier.
Data Analysis: Listening barriers were compiled into barrier “factors” in order for the data to be analyzed effectively. “Laziness” defined by students’ lack of effort put into listening to a complex topic was the most frequently cited barrier factor by students.
Lauer & Asher: True Experiments
Uses treatments and control groups. Randomization is an important part of the research design. A Hypothesis is claimed. Pretests for each group can ensure that the groups were randomized.
type 1 error – research says something was stat sig, but this was only due to chance
type 2 error – researcher says something wasn’t stat sig, but it really was
internal validity threats – instrumentation, measurement, regression towards the mean, mortality, maturation, selection, history, instability, psych threats
external validity – the “generalizableness” of research
Lauer & Asher: Quasi Experiments
How is it not a true experiment? There is no randomization, it must have a pretest to see that groups are equal, and there must be research design hypothesis to account for ineffective treatments.
2 types: strong (high equality between groups) and weak quasi experiments
Other types of quasi experiments: time-interrupted, repeated treatment, regression-discontinuity
Quasi experiments can produce strong results when true experiments are not possible
Carroll et al.: The Minimal Manual
This research showed that shorter manuals often result in better understanding of the material. The researchers first tried to design a shorter, minimal handbook and then tested to see if users were able to improve their learning of the software when using it.
Research Question: Would a minimal manual help users learn and complete tasks easier?
Subject Selection: Used 19 people who had experience with routine office work and little computer experience
Data Collection: In a realistic office environment, subjects were asked to complete 8 tasks with the software in able to learn it
Data Analysis: Researchers compared learners with a standard software training manual with learners with a designed minimal manual. Subjects were scored on the completion of tasks and how quickly they were able to do so.
Subject Selection: 32 subjects were used, 8 for each category. Again, they wanted subjects with routine office work experience and little computer experience.
Data Collection: Used a 2 x 2 research design to compare a standard manual with a minimal manual, each with w types of learning: learning by the book and learning with tasks approaches. Learners were monitored while they attempted to complete 6 tasks. They were encouraged to think aloud.
Data Analysis: Subjects were scored on the successful completion of tasks and how quickly they were able to do so. Researchers also measured how quickly learners started the system and what errors they encountered. A taxonomy of error types was developed during the pilot study to be able to categorize these errors.
Notarantonio & Cohen: The Effects of Open and Dominant Communication Styles on Perceptions of the Sales Interaction
Research Question: How would students rate sales pitches from salespeople with low or high dominance and high or low openness?
80 Subjects in this research were chosen from business school.
Videotaped questionnaires and subject’s self reports on their communication styles were used
Answers were compiled together and analyzed based on which video they watched. 2 x 2 research design showed that high-low combinations worked, but salespeople with either a high-high, or a low-low combination of dominance and openness were viewed unfavorably by students
Kroll: Explaining how to Play a Game: The Development of Informative Writing Skills
Research Question: How do students of various ages use writing to explain a task?
Subject Selection: Students in grades 5, 7, 9, 11, and college freshmen were chosen as subjects.
Data Collection: Subjects were shown a video explaining how to play a game and then were told to write explanations of the game. 2 researchers evaluated the student’s explanations, with one of these being aware of the study.
Data analysis: Scores for the student’s explanatory ability were analyzed based on their grade level. Researchers also looked at the student’s ability to explain 10 different elements of the game.