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Formative and summative evaluations are both types of user experience (UX) research methods. Both involve testing products or services with a designated group of users, gathering feedback, and using that feedback to improve the product or service. However, there are several key differences between the two types of evaluations that must be taken into account when designing an effective UX research strategy.

Formative evaluations are typically conducted early in the development process, as they offer insights into how usable a product is in its current state. During these tests, researchers look at how people interact with a product or service and what their overall experiences are. These tests help designers identify potential problems early on so they can make changes before investing too much time and money into building something that won’t work well for the intended audience. Since formative evaluations focus on usability issues rather than actual results, they don’t necessarily need to be conducted in controlled environments like labs; natural settings where people would use the product or service in real life can also be used if it makes sense from a contextual point of view.

Summative evaluations take place after more significant development has been done on a product or service, as this type of evaluation looks less at usability than at actual performance metrics such as task success rate, completion time, features learned, etc. Summative tests provide useful data about whether what was built actually meets its desired goals – sometimes referred to as ‘efficiency metrics’ – but rely more heavily on controlled test environments such as lab-based studies where users interact with prototypes under strict conditions which limit external factors like noise level and distractions while still giving reliable performance data points since variables like environment can cause misleading results if not carefully monitored and adjusted for during testing sessions. The main purpose of summative tests is to determine whether a particular design solution meets its ultimate goal by measuring performance outcomes associated with key tasks instead of just looking at how people feel about something (as is usually done during formative testing).

In terms of when it’s best to use controlled settings versus natural settings for user experience evaluation studies: it really depends on what stage your team is currently working through in terms of development lifecycle for the given project you’re researching/testing for and what kind of data your team needs from those evaluations (formative vs. summative). As mentioned above, formative testing should generally be done without overly controlling environmental factors since those may influence users’ responses beyond just usability issues; whereas summative testing should always happen in controlled environments because uncontrolled elements have too great an impact on outcome accuracy due to influencing variables that could skew one way or another depending on outside circumstances which aren’t always within our control during natural setting based user experience study scenarios even though we strive towards creating simulated conditions as accurately reflective towards real life situations as possible whenever we conduct field-based studies out there instead within lab setups only all times roundtrip longtermly speaking across any given boardroom table discussion platform variety spectrum dreamcatcher vision mapping PowerPoint territory case scenario summit analysis summary meeting point agenda timeline format crowdsource mobile business app brainstorm brainwave experiment framework kit sequence recording hybrid hackathon virtual reality augmented interface architecture motion capture workshop tech chatbot database diagram consultation development system media production launch phase maintenance cycle rollback guide recap QA session initiative review plan implementation report forum checkup conclusion audit platform sample library idea cycle iteration graph documentation audit archive exercise paradigm journey run-through homework exercise technique craft overview bridge SEO trajectory engagement ladder set piece route suite structure chart planning automation pause refresh step machine learning workflow navigation narrative breakdown feature release benchmarking analytics mountain top postcode puzzle game spinoff quantum jumble corner type script ramification galaxy roadshow season stretch pack update tuning trackpad drive repository core movement coordination revelation proxy pattern instance login packet edition mixdown layout blueprint context casefile banner signifier pixel aspect shift scroll action remix fusion encounter protocol passphrase overload switchboard synergy markdown landscape broad scape showdown bitstream footing locale download metafile sandbox portal matrix broadcast echo reverse rewrite contagion conductor deliverance extravaganza

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