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Experimental research design and methodology in TPR. PhD Course in Translation Process Research Copenhagen, July 2014. Outline. Research design – basic concepts Experimental tools and methods to collect translation process data Examples of experimental TPR studies
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Experimental research design and methodology in TPR PhD Course in Translation Process Research Copenhagen, July 2014
Outline • Research design – basic concepts • Experimental tools and methods to collect translation process data • Examples of experimental TPR studies • Some practical considerations about carrying out experiments
Outline • Research design – basic concepts • Experimental tools and methods to collect translation process data • Examples of experimental TPR studies • Some practical considerations about carrying out experiments
Design Starting point: I-wonder-question Rephrase as research question/hypothesis Consider What type of question/hypothesis it is Sample and population Which variables are involved
Design Starting point: I-wonder-question Rephrase as research question/hypothesis Consider What type of question/hypothesis it is Sample and population Which variables are involved
Design: Research question/hypothesis • Formulate your I-wonder-question clearly and unambiguously • Make it falsifiable • Consider whether your starting point is • Question: Is there a difference between students and professional translators in terms of ST reading? • Open hypothesis: There is a difference between students and professionals in terms of ST reading • Directional hypothesis: There is a difference between students and professional translators in terms of ST reading, such that professionals spend less time on the ST
Design Starting point: I-wonder-question Rephrase as research question/hypothesis Consider What type of question/hypothesis it is Sample and population Which variables are involved
Design: Type of question/hypothesis • Differences • Repeated measures: measuring effect of some difference within one group, e.g. • same translatorsworking under differentconditionsor over a period of time (longitudinalstudy) • Independent groups: group difference between different groups doing same task, e.g. • students vs. professionals • training vs. controlgroup • Functional relations • Between response and some manipulated variable
Design Starting point: I-wonder-question Rephrase as research question/hypothesis Consider What type of question/hypothesis it is Sample and population Which variables are involved
Design: Sampling and population • Inferential statistics assumes random sampling • In practice, balance between randomness and possibility • Consider population and sample • Which population does my question pertain to? • Is it realistic to sample from that population? • Could a realistic sample pertain to a different, but still relevant population?
Design Starting point: I-wonder-question Rephrase as research question/hypothesis Consider What type of question/hypothesis it is Sample and population Which variables are involved
Design: Variables Two important distinctions Independent/explanatory (EV), dependent (DV) and control (CV) variables Categorical and numerical variables
Design: DVs • Dependent/response variable (DV): what you are measuring or counting, e.g. • Translation time • Overall • Individual fixations • Translation quality • Number of occurrences of e.g. • metaphors • specific syntactic constructions • …
Design: EVs • Independent/explanatory variables (EVs): • Variables which according to your hypothesis may have an effect on your DV • Also called predictors • Types • Item-related: e.g. task difficulty, translation direction, translation tool • Participant-related: e.g. sex/gender, L1, professional status, L2 experience
Design: CVs • Control variables (CVs): variables to control in order to be sure that EV is responsible for DV • Experimental control • Statistical control • Avoid confounds
Design: Categorical and numerical variables • Categorical • Unordered categories (nominal): e.g. sex/gender, word class • Ordered categories (ordinal): e.g. lower/middle/upper class • Numerical • Discrete • Integers, finite values • E.g. counts of word in a corpus • Continuous • Real numbers, infinitely many values on scale • E.g. reading time
Design: Categorical and numerical variables Translation experiencemaybeconstrued as • Nominal scale: student/professional • Ordinalscale: beginning / advanced student / professional • Discretenumerical: number of years of experience (1, 2, 3, 4…) • Continuousnumerical: amount of experience (time, output)
Design: Categorical and numerical variables Importantramifications for • The questionsasked • The type of statistical test to beapplied
Outline • Research design – basic concepts • Experimental tools and methods to collect translation process data • Examples of experimental TPR studies • Some practical considerations about carrying out experiments
Experimental TPR tools and methods • eye-tracking • keylogging • audio recording (in Translog) • (video recording) • (think-aloud protocols) • retrospective interviews and questionnaires
Eye-tracking • eye-mind assumption (Just and Carpenter 1980) • cogntive attention • cognitive load • areas of interest (AOI) • eye-tracking measures • fixation count • total gaze time • fixation duration • pupil dilation • eye movements (transitions, attention shifts)
Keylogging • transient versions of target text • revision/editing • navigation • pauses • production speed • final target texts
Audio recording (available in Translog) • oral translations • think-aloud • comments
Questionnaires/retrospective interviews • language background • professional background • perception of source text difficulty • perception of different tasks • translation challenges experienced • etc.
Assessing the product • translation quality assessments • examination of translation of individual words (e.g. metaphors, terminology, specific word classes, number of alternative translation solutions, etc.)
Outline • Research design – basic concepts • Experimental tools and methods to collect translation process data • Examples of experimental TPR studies • Some practical considerations about carrying out experiments
Example 1: goal • to find out (‘I wonder’) how translators, with no post-editing training, would perform when asked to post-edit MT-produced output in comparison with the performance of a group of translators who translated the same texts manually, without any dictionary or technical assistance.
Example 1: research questions • what are the differences in quality between manual translations and post-edited MT output? • do more corrections lead to higher quality in the post-edited texts? • what are the time differences between manual translations and post-editing? • what are the differences in allocation of cognitive resources between manual translation and post-editing
Example 1: design/set-up • experimental research design with manipulation of circumstances to measure the effect on participants’ behaviour • lab environment simulating natural conditions • translation rankings
Example 1: variables • Dependent/response variables • translation time • translation quality • allocation of cognitive resources (ST vs. TT) • Independent/explanatory variable • translation mode (manual translation vs. post-editing)
Example 1: variables • control variables • using the same participants with the same text for both tasks might have created an unintended repetition effect • using the same participants but different texts might have created an unintended effect of textual differences (e.g. one text more difficult than the other)
Example 1: experiments • Modes • manual translation and post-editing • Participants • 8 translators and 7 post-editors • Texts • three English source texts (same for both groups)
Example 1: experiments • one group of participants translated three texts (from scratch) from English into Danish and • one group of participants post-edited machine-translated (Google Translate) Danish versions of the the same three source texts
Example 1: tools/methods • eye-tracking • allocation of cognitive resources (total gaze time on ST vs. TT) • keylogging • task time • keystrokes (edit distance) • final output • translation evaluations • translation quality
Example 1: quality assessment • QA method and procedure • 7 evaluators • presentation of source sentence together with four candidate translations • two sentences had been produced using manual translation and two had been produced using post-editing (randomised and blinded) • evaluators were instructed to rank candidate translations from best to worst quality (ties permitted). • inter-rater and intra-rater agreement • did evaluators agree with each other • were evaluators consistents in their rankings
Example 1: design weaknesses • sample size • participant qualifications (not all worked as professional translators) • quality assessments (assessment task too difficult, inter-rater and intra-rater agreement too low)
Example 2: Speaking your translation students’ first encounter with speech recognition technology
Example 2: goal • to measure the impact on the translation process and product of using an automatic speech recognition (ASR) system compared with typing a translation and producing a sight translation without ASR • to measure the effect of training/practice with ASR on task time and quality of translations produced with ASR
Example 2: research questions (quantitative) • What are the task times in the three translation modalities (written, sight, ASR)? • Is there any difference in translation quality in the three modalities? • Is there any difference in cognitive load? • What is the effect on time and quality of participants training the system and gaining more experience using it?
Example 2: research questions(qualitative) • What are the students’ own perception of working with an ASR system? • What kind of strategies are employed by students who experience positive effects on time and quality?
Example 2: design/set-up • experimental research design with manipulation of circumstances to measure the effect on participants’ behaviour • lab environment • analysis of process and product • longitudinal study • experimental group compared with control group • qualitative analyses
Example 2: variables • Dependent/response variables • translation time • translation quality • cognitive load (average fixation durations) • Independent/explanatory variables • translation mode (written, sight, ASR) • training period
Example 2: variables • Control variables • texts had to be as similar as possible to ensure that process/product differences across translation tasks were caused by the mode and not by the text • sequence of presentation was rotated to ensure that differences between the written and oral modalities were owing to the translation mode and not, for instance, to varying levels of difficulty
Example 2: experiments • participants • 14 translation students divided into two groups of seven: an experimental (training) group and a control group • modes • written translation • sight translation • sight translation with speech recognition • text • text excerpts taken from the same longer text to ensure the highest possible level of similarity
Example 2: experiments • Longitudinal study: • phase 1 (baseline): all participants translated texts under three different conditions • interim period: half of the participants (experimental group) worked with the ASR program at home (partly under controlled conditions) and the other half did not (control group) • phase 2 (follow-up): all participants translated texts under three different conditions (similar to phase 1), and results from experimental group were compared with control group and related to phase 1
Example 2: tools/methods • eye-tracking • cognitive load (fixation duration) • Translog • timings • oral and written output • transient versions of oral and written translations • evaluations of translation output • translation quality • retrospective interviews • students’ perceptions of ASR vs. written/sight