| Collection period: |
| Date from: | Date to: |
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| 15 January 2014 | 30 April 2015 |
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| Geographical area: |
Bangkok, Thailand |
| Country: |
Thailand |
| Data collection method: |
A normative data collection method was used, based on similar methods used in previous research studies (Snodgrass & Vanderwart, 1980; see also, Alario & Ferrand, 1999; Brodeur et al., 2010; Guérard et al., 2015). Instructions as well as all relevant procedural information were delivered in Thai.
A total of 584 undergraduate students (235 males, 349 females; mean age = 19.14 years, SD = 1.06; mean years of education = 13.22 years, SD = 2.02) from Thammasat University and Chulalongkorn University provided ratings for the 480 colour photographic images from the Bank of Standardized Stimuli (Brodeur et al., 2010), on seven normative dimensions: name agreement, image agreement, category agreement, object familiarity, visual complexity, two indices of manipulability, and age of acquisition. All participants were native Thai speakers and volunteered or received a small payment for their participation.
Testing took place in groups of between 10 and 30 participants. For some tasks, participants recorded their responses using 5-point Likert scales: image agreement (1 = low agreement, 5 = high agreement); object familiarity (1 = very unfamiliar, 5 = very familiar); visual complexity (1 = very simple, 5 = very complex); and manipulability (graspability, 1 = very difficult to grasp, 5 = very easy to grasp; mimability, 1= very difficult to mime, 5 = very easy to mime). All stimuli were displayed sequentially via an overhead projector on a large, white screen at the front of a large classroom. Image presentation was fully randomized for each variable and for each group of participants.
In the image agreement task, participants rated how well an object name matched its associated picture, by forming an image in response to the object name and then rating how closely their mental image matched the picture that followed. In the object familiarity task, participants based their ratings on how often they came into contact with or thought about the concept that was depicted by the object. Visual complexity was defined as the amount of detail or intricacy of lines that were used to depict the object in each picture. In the manipulability task, two types of ratings were collected. For graspability, participants rated the ease with which they could grasp each object for the purpose of moving it; for mimability, participants rated each item according to the ease with which they could mime its use when alone. Slightly different procedures were employed for the remaining variables. In the name agreement task, participants generated object names by writing down the name of the first Thai word that came to mind. Naming failures were also recorded, with three categories used (don’t know object, don’t know name, tip-of-the-tongue). In the category agreement task, participants determined an object's category membership by assigning a single number to each picture as it was presented. The following 19 pre-defined categories (Brodeur et al., 2010) were translated into Thai: building materials, clothing, decoration and gift accessories, electronic devices and accessories, food, furniture, games, toys and entertainment, hand labor tools and accessories, household articles and cleaners, jewels and money, kitchen utensils, medical instruments and accessories, musical instruments, natural elements and vegetation, outdoor activity and sport items, skin care and bathroom items, stationery and school supplies, weapons and items related to war, and other. In the age of acquisition task, participants estimated the age at which they had first learned the names of the objects (the names being the modal names generated in the name agreement task). Age-of-acquisition ratings were made using a 7-point scale (Gilhooly & Logie, 1980), with each point representing an age range of two years (1 = 0–2 years old; 2 = 3–4 years old; 3 = 5–6 years old; 4 = 7–8 years old; 5 = 9–10 years old; 6 = 11–12 years old; 7 = 13 years old or older).
Once they completed the study, all participants provided demographic information (e.g., age, gender, years of education, native language) in a questionnaire. They were then debriefed and thanked for their participation.
All participants gave informed consent and understood that they could withdraw at any time during the research study without any consequences. Data were collected anonymously thus it was impossible to identify individual participants in any way from the data they contributed to the Thai psycholinguistic norming study. |
| Observation unit: |
Individual, Object, Text unit |
| Kind of data: |
Numeric, Numeric, Text |
| Type of data: |
Experimental data
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| Resource language: |
English, Thai |
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| Data sourcing, processing and preparation: |
For object familiarity, visual complexity, manipulability, image agreement, and age of acquisition, scores were computed by averaging responses across items. For name agreement, written name responses with any obvious misspellings were corrected. All classifiers, quantifiers, and any other descriptors that brought no additional meaning to the response were removed (e.g., in the context of pot to boil hot water a transliteration of the Thai phrase for coffee pot, the word hot was a redundant descriptor given for boiled water, so was removed). Responses with added elaborations (descriptions which add specificity, precision, or further meaning; e.g., box in Tupperware box) were treated as different responses. Commonly acceptable abbreviations (e.g., TV and television) were treated as different responses because they could develop subtle semantic variances from parent words over time (see Snodgrass & Vanderwart, 1980). Word order differences (e.g., horse doll and doll horse) were only regularized if their meanings were judged as identical by a Thai semanticist. Finally, some pairs of responses seemed highly similar in meaning and these were considered independently by two native Thai speakers. Words judged equivalent in meaning by both judges were further discussed with the same Thai semanticist to determine how they should be coded (e.g., vegetable broccoli vs. broccoli; almond nut vs. almond). As a result of these discussions, some semantically identical responses were regularized.
Two indices of name agreement were computed: percentage name agreement (i.e., the most frequently occurring name for each object) and the information statistic H (see Snodgrass & Vanderwart, 1980), which captures more information about the distribution of names across participants than percentage name agreement. For the category agreement task, the modal category, percentage category agreement, and corresponding H value (Hcat) were computed using the same procedures described above. Naming failure rates (DKO, DKN, and TOT) were calculated as the total number of naming errors (1774) divided by total number of possible responses (14,400).
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| Rights owners: |
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| Contact: |
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| Publisher: |
UK Data Archive
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| Last modified: |
17 Jan 2017 14:06
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