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Library Hi Tech
ISSN : 0737-8831
Article publication date: 8 July 2022
Issue publication date: 22 August 2022
This paper attempts to provide significant information on the increased growth of literature of chatbots and virtual assistants. Technological changes are dynamic and keep changing at regular intervals. Therefore, it becomes highly crucial to review the performance of chatbots and virtual assistants. This paper aims to review the literature by eminent researchers in the form of authors, keywords and major contributing organizations.
Systematic literature review and bibliometric analysis is used to analyze the growth of literature on chatbots. A sum of articles has been extracted from Scopus database with selected keywords and with certain filters. VOSviewer software is used for analysis of data. A total of 130 documents are extracted from Scopus database from 2017 to 2021 (31st August).
This study provides a significant contribution to an existing literature and provides the understanding of research in the area of chatbots and virtual assistants. The authors with maximum number of citations are Yan, Zaho, Bengio, Weizenbaum, Song, Zhou and Maedche with jointly 180 citations. Research is been contributed by different countries where the United States is the country with highest number of documents published. The United States contributes 17% of the total production in the area of chatbots and virtual assistants. The analysis shows that the area is gaining momentum as contribution in this area is been increasing in last few years.
The study shows that several branches of chatbots are also in mainstream like natural language processing, e-learning, behavioural research, conversational agents, virtual assistants, human–computer interaction, natural language and so on. It provides a wider scope to authors and researchers to gain useful insights. The bibliometric study will provide a broader spectrum in this area.
The developments in technology and also the effect of COVID-19 pandemic is boosting the adoption of technology in different sectors. Deployment of technology will uplift the economy and social infrastructure. Society can avail different services from their comfort area and also in real time. This will help in reducing wastage of resources like people visiting offices for routine jobs which can be easily availed from their workplace. Society may access better services without much human interaction.
This paper adds significant contribution to the existing literature by analysing the published papers from Scopus database. The study contains new and significant information as this study covers all industries where chatbots and virtual assistants are being applied whereas in previous literature only specific industry has been taken into consideration.
- Virtual assistants
- Systematic literature review
- Bibliometric analysis
Agarwal, S. , Agarwal, B. and Gupta, R. (2022), "Chatbots and virtual assistants: a bibliometric analysis", Library Hi Tech , Vol. 40 No. 4, pp. 1013-1030. https://doi.org/10.1108/LHT-09-2021-0330
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A Systematic Review of Voice Assistant Usability: An ISO 9241–11 Approach
Faruk lawal ibrahim dutsinma.
1 Innovative Cognitive Computing (IC2) Research Center, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand
2 School of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand
Jonathan H. Chan
Voice assistants (VA) are an emerging technology that have become an essential tool of the twenty-first century. The VA ease of access and use has resulted in high usability curiosity in voice assistants. Usability is an essential aspect of any emerging technology, with every technology having a standardized usability measure. Despite the high acceptance rate on the use of VA, to the best of our knowledge, not many studies were carried out on voice assistants’ usability. We reviewed studies that used voice assistants for various tasks in this context. Our study highlighted the usability measures currently used for voice assistants. Moreover, our study also highlighted the independent variables used and their context of use. We employed the ISO 9241-11 framework as the measuring tool in our study. We highlighted voice assistant’s usability measures currently used; both within the ISO 9241-11 framework, as well as outside of it to provide a comprehensive view. A range of diverse independent variables are identified that were used to measure usability. We also specified that the independent variables still not used to measure some usability experience. We currently concluded what was carried out on voice assistant usability measurement and what research gaps were present. We also examined if the ISO 9241-11 framework can be used as a standard measurement tool for voice assistants.
Voice assistants (VAs) which are also called intelligent personal assistants are computer programs capable of understanding and responding to users using synthetic voices. Voice assistants have been integrated into different technological devices, including smartphones and smart speakers [ 1 ]. The voice modality is the central mode of communication used by these devices, rendering the graphic user interface (GUI) inapplicable or less meaningful [ 2 ]. People use VA technology in different aspects of their lives, such as for simple tasks like getting the weather report [ 3 ] or managing emails [ 4 ]. In addition, the VA can perform complex tasks like client representative tasks [ 5 ] and controllers in autonomous vehicles [ 6 ]. In other words, VA’s can revolutionize the way people interact with computing systems [ 7 ]. Currently, there is a massive global adoption of voice assistants. A report in [ 8 ] indicates that 4.2 billion VA’s were adopted and used in 2020 alone, with a projected increase to 8.4 billion by 2024. The popularity of VA’s has led to a greater research attention to its usability and user experience aspect.
Usability is a critical factor in the adoption of voice assistants [ 9 ]. A study by Zwakman et al. [ 10 ] highlighted the importance of usability in voice assistants [ 9 ]. An additional study by Coronado et al. [ 11 ] reiterated the importance of usability in human–computer interaction tools. Numerous studies have been carried out on the usability heuristics used in a VA, each study adopting a unique approach. A study by Maguire [ 12 ] used the Nielsen and Molich versions of Voice User Interface (VUI), and the heuristic Voice User Interface (VUI), to evaluate the ease of use of the VA’s. The study affirmed both the two heuristics were appropriate. However, the study noted that one was less problematic to use than the other [ 12 ]. A further study tested VUI heuristics to measure VA efficacy [ 13 ]. However, a critical factor that prevents the VA from adopting the heuristic currently available is the absence of a graphical user interface (GUI). Despite numerous studies on heuristics, the level of satisfaction is still low [ 14 ]. Furthermore, heuristics cannot be used as a standardized approach because they are approximate strategies or empirical rules for decision-making and problem-solving that do not ensure a correct solution. According to a study by Murad [ 16 ], the absence of standardized usability guidelines when developing VA interface presents a challenge in the development of an effective VA [ 15 ]. Another report from Budi & Leipheimer [ 17 ] also suggests that the usability of the VA’s requires improvements and standardization [ 16 ]. To create a standard tool a globally recognized and well-known organization is critical in the process because it eliminates bias and promotes neutrality [ 17 ]. The International Organization for Standardization (ISO) 9241-11 framework is one of the standard usability frameworks widely used for measuring technology acceptance.
According to the ISO 9241–11 framework, usability is defined as “the degree to which a program may be utilized to achieve measurable objectives with effectiveness, efficiency, and satisfaction in a specific context of usage” [ 18 ]. ISO 9241-11 provides a framework for understanding and applying the concept of usability in an interactive system and environment [ 19 ]. The main advantage of using the ISO standard is that industries and developers do not need to build different design measurement tools. This standard is intended to create compatibility with new and existing technologies, and also create trust [ 20 ]. Currently, the system developers do not have any standardized tool created specifically for the measurement of VA usability, consequently, the measures are decentralized, causing confusion among developers. The lack of in-depth assessment of the current heuristics used in the VA design affects the trust and adaptability of their users [ 15 ]. Other emerging technologies such as virtual reality [ 21 ] and game design [ 22 ] have understood the importance of creating an acceptable standardized measurement tool when designing new interfaces. Therefore, VA technology could also benefit significantly from the same concept. As evident from the above discussion, there is little to no focus on VA standardization.
Our study presents a systematic literature review comprising works carried out on the usability of voice assistants. In addition, we use the ISO 9241-11 framework as a standardized measurement tool to analyze the findings from the studies we collected. We chose the ACM and IEEE databases for the selection of our articles because both contain a variety of studies dealing with the usability aspects of VA’s. The following are the contributions of this literature review to the Human--Computer Interaction (HCI) community:
- Our work highlights the studies currently carried out on VA usability. This includes the independent and dependent variables currently used.
- Our study highlights the factors that affect the voice assistants' acceptance and impact the user’s total experience.
- We identify and explain some attributes unique to only voice assistants, such as machine voice.
- We also highlight the evaluation techniques used in previous studies to measure usability.
- Finally, our study tries to compare the existing usability studies with the ISO 9241-11 framework. The decentralized approach of the VA usability measurement makes it vague to understand if the ISO 9241-11 framework is being adhered to whilst developing the usability metrics.
We hope that our input will highlight the integration of the current existing VA usability measures with the ISO 9241-11 framework. This will also verify whether the ISO 9241-11 framework can serve as a standard measure of usability in voice assistants. In conclusion, our study tries to answer the following four research questions:
- RQ 1 : Can the ISO 9241–11 framework be used to measure the usability of the VA’s?
- RQ 2 : What are the independent variables used when dealing with the usability of VA’s?
- RQ 3 : What current measures serve as the dependent variables when evaluating the usability of VA’s?
- RQ 4 : What is the relationship between the independent and dependent variables?
The remaining work is structured as follows. The second section presents the related work. This highlights what previous literature review studies had been carried out on voice agents’ usability; furthermore, the section also highlights the emergent technology that employed the ISO 9241-11 framework as a usability measuring tool. This is followed by the methodology section, which presents the inclusion and exclusion criteria used together with the review protocol. Furthermore, the query created for the database search is presented, and the database to be used is also selected. The fourth section presents the result and analysis. In this phase, the article used for this study is listed. Also, the research questions are answered. The fifth section contains discussion on the result analysis. This includes a more detailed explanation of the relationships between independent and dependent variables. Our insights and observations are included in this section as well.
Previous systematic reviews.
There have been a number of systematic literature reviews concerning VA’s over the years. Table Table1 1 presents the information for a few of the relevant works.
Current literature reviews
As highlighted in Table Table1, 1 , multiple systematic literature reviews have been carried out on VA's usability over the years. However, each study has a specific limitation and gap for improvement. For instance, some studies focus on the usability of voice assistants used only in specified fields such as education [ 25 ] and health [ 36 ]. Other studies focus on the usability of voice assistants concerning only specific age groups, such as older adults [ 28 ]. Likewise, although an in-depth analysis of the usability of the VA’s is carried out involving every usability measure in [ 32 ], this study does not use the ISO 9241 framework as a measuring standard. On the other hand, another study in [ 33 ] although uses the ISO 9241 framework as a measuring standard, however, the usage context was chatbots focusing primarily on text-based communication instead of voice. Overall, the available literature reviews on VA’s usability listed in Table Table1 1 supports the view that very few of the current literature review studies on VA’s use the ISO 9241-11 framework as an in-depth tool for measuring usability.
The ISO 9242-11 Usability Framework
The ISO 9241-11 is a usability framework used to understand usability in situations where interactive systems are used and employed, which includes framework environments, products, and services [ 39 ]. Nigel et al. [ 40 ] conducted a study to revise the ISO 9241-11 framework standard, which reiterates the importance of the framework within the concept of usability. A number of studies have been conducted on various technologies using the ISO 9241–11 framework as a tool to measure their usability. This shows the diversified approach when using the framework. For instance, a study by Karima et al. (2016) proposed the use of ISO 9241-11 framework to measure the usability of mobile applications running on multiple operating systems by developers, in which the study identified display resolution and memory capacity as factors that affect the usability of using mobile applications [ 41 ]. Another study used the ISO 9241-11 framework to identify usability factors when developing e-government systems [ 42 ]. This study focused on the general aspect of e-Government system development and concluded the framework could be used as a usability guideline when developing a government portal. In addition, the ISO 9241-11 framework was also used to evaluate other available methods and tools. For instance, a study by Maria et al. [ 44 ] used the framework to evaluate existing tools used in the measurement of usability of software products and artifacts on the web. The study compared existing tools with the ISO 9241-11 measures for efficiency, effectiveness and satisfaction [ 43 ]. ISO 9241–11 framework has also been employed as a method of standardization tool in the geographic field [ 44 ], game therapy in dementia [ 45 ], and logistics [ 46 ]. Despite the ISO 9241-11 usability framework being utilized in different aspects of old and emergent technologies, it has not been used with a VA in the past.
We performed a systematic literature review is this study using the guidelines established by Barbara [ 47 ]. These guidelines have been widely used in other systematic review studies as a result of their rigor and inclusiveness [ 48 ]. In addition, we have added a new quality assessment process to our guidelines. The quality assessment is a list of questions that we use to independently measure each study to ensure its relevance for our review. Our quality evaluation checklists are derived from existing studies [ 49 , 50 ]. The complete guidelines used in this section comprises of four different stages:
- Inclusion and exclusion criteria
- Search query
- Database and article selection.
- Quality assessment.
Inclusion and Exclusion Criteria
The inclusion and exclusion criteria used in our study are developed for completeness and avoidance of bias. The criteria we used for our study are:
- Studies that focus on VA, with voice being the primary modality. In scenarios where the text or graphical user interfaces are involved, they should not be the primary focus.
- Studies are only in the English language to avoid mistakes during translation from another language
- The studies include at least one user and one voice assistant to ensure that the focus is on usability, not system performance.
- Study has a comprehensive conclusion.
- Released between 2000 and 2021, because during this period the vocal assistants started to gain notable popularity
The exclusion criteria are:
- Studies with poor research design, where the study's purpose is not clear are excluded.
- White papers, posters, and academic thesis are excluded.
We created the search query for our study using keywords arranged to search the relevant databases. We went through previous studies to find the most relevant search keyword to find what is commonly used in usability studies. After numerous debates among the researchers and seeking two HCI expert's opinion, we chose the following set of keywords: usability, user experience, voice assistants, personal assistants, conversational agents, Google Assistant, Alexa, and Siri. We connected the keywords with logical operators (AND and OR ) to yield accurate results. The final search string used was (“usability” OR “user experience “) AND (“voice assistants” OR “personal assistants” OR “conversational Agents” OR “Google Assistant” OR” Alexa” OR “Siri”). The search was limited to the abstract and title of the study.
Database and Article Selection
Figure 1 highlights the graphic presentation of the selection and filtering process. The figure is adapted from the Prisma flow diagram [ 51 ]. As earlier stated, two databases are used as the sources for our article selection: the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE). Both databases we used in our study contain the most advanced studies on VA and are highly recognized among the HCI community. The search query returned 340 results from the ACM database and 280 results from the IEEE database. 720 items in both databases were checked for duplication and 165 documents (23%) were found to be duplicated and hence removed. Additionally, more items were filtered by title and abstract. We utilized keyword match to search the title; however, the abstract was read to identify the eligibility criteria. In addition, 399 documents (72%) were removed because they did not meet the eligibility criteria. Finally, 121 documents were removed that were not consistent with the research objectives of our study. At the end of the screening process 29 articles (19%) were finally included in this literature review.
Article selection process
The selected items presented in Table Table2 2 are used for assessing the quality of the selected articles. The process was deployed to ensure the reported contents fit into our research. The sections collected from articles such as the methodology used, analysis done, and the context of use within each article were vital to our study. Each question is a three-point scale: “Yes” is scored as 1 point, which means the question is fully answerable. “Partial” is scored as 0.5, which means the question is vaguely answered, and “NO “is scored as 0, which means it is not answered at all. All the 29 sets of finally included articles passed the quality assessment phase.
Quality assessment checklist
Result and Analysis
List of articles.
This section lists and discusses the articles collected in the previous stage. Table Table3 3 presents the list of all the compiled articles. Moreover, we identified the usability focus of each study.
List of compiled articles
Voice Assistant Usability Timeline
We grouped the collected research into three categories, each representing a range of time frames (Fig. 2 ). The categorization is based on voice assistant period breakthroughs. The first category is from 2000 to 2006, which was the year of social media and camera phones, also known as the year of the Y2K bug in telecommunications. During these years, conversational agents started to get noticed with the introduction of the inventions such as the Honda’s Advanced Step in Innovative Mobility (ASIMO) humanoid robot [ 80 ]. The second category ranges from 2007 to 2014. During these years technological advancements got users more exposed to voice assistants through embedding them into smartphones and computers. For instance, Apple first introduced SIRI in 2011 [ 81 ], and Microsoft introduced Cortana in 2014. The last category ranges from 2015 to 2021. This was when the massive adoption of voice assistants took place, making it an all-time high.
Year of publication of selected articles
Based on the year of publication of our selected articles, Fig. 2 clearly shows that the study on VA’s has expanded significantly over the last six years (2014–2021). This can be attributed to the invention of a smart speaker and phone with built-in voice agents [ 82 ]. Another reason for VA popularity is the COVID -19 outbreak that has given a fresh impetus towards touchless interaction technologies like voice [ 83 ].
Different Embodiment Types of VA’s
Smart speakers are the mostly used embodiment of VA’s used in our selected articles. This is due to the current popularity of commercial smart speakers such as Alexa, HomePod, etc. A 2019 study showed that 35% of US households have an intelligent smart speaker, and projected to reach 75% by 2025 [ 84 ]. Use of humanoids is also popular because usability measures such as anthropomorphism are essential for voice assistant usability [ 85 ]. Furthermore, Fig. 3 shows that only a few studies were done on car interface voice assistants. Car interfaces are vocal assistants that act as intermediaries between the driver and the car. The VA car interface allows drivers to access car information and also be able to perform the task without losing focus on driving. The fourth type of software interface refers to a voice assistant software embedded inside smartphones or computers. The studies we have collected have used either the commercialized form of the software interface, such as Alexa and Siri, while others have developed new voice interfaces that are easily accessible to users due to the adoption of smartphones and computers assistants using programming codes and skills. Nevertheless, both are in the forms of different software agents.
Embodiment of Voice assistant used in selected studies
Component of ISO 9241-11 Framework
The ISO 9241-11 framework highlights two components, the context of use and usability measure [ 18 ]. We concentrate on both components to highlight any correlations between usability metrics and the context of use in the selected articles. The context of use consists of the different independent variables along with the techniques used for analyzing them. Likewise, the usability measure represents the dependent variables, i.e., the effect that the independent variables have on the overall experience of the users. Accordingly, the analysis is presented in a bi-dimensional manner in the following sections.
Context of Use
We split the context of use into an independent variable and the techniques used. The independent variables presented in our study are the physical and mental attributes used to measure a given user interaction outcome. Furthermore, our study grouped the independent variables into five main categories. The grouping is shown in Fig. 4 and is based on the similar themes identified from the collected studies. The five groups included people (user attributes), voice (voice assistant attributes), task, conversational style, and anthropomorphic cues. The voice and people categories are the oldest independent variables used to measure usability. Their relevance is also seen in the recent studies, which indicate that researchers have a high interest in correlating users with the VA’s. On the other hand, anthropomorphic clues and conversational styles are relatively new to the measurement of usability. The task-independent variable is the most used variable of late, perhaps because users always test the VA’s ability to perform certain tasks. It also indicates that VA’s are widely used for various functional and utilitarian aspects. The anthropomorphic cues are seldom used in the second phase (2007–2014). However, it is most widely used in the last range (2015–2021).
Categories of independent variable use over the years
In Table Table4 4 we highlight more details with regards to the different groups of the independent variable collected, and also present examples of the independent variables for each category. We highlight how the independent variables have been applied by the previous studies and in which environment they have been used. We defined each independent variable category in Table Table4, 4 , and explained their sub-categories as well. As evident from Table Table4, 4 , different independent variables are used together in multiple studies. For example, independent voice variables and independent people variables are used simultaneously in various studies, such as personality, gender, and accent. Similarities between multiple independent variables aid to understand the relationship between the variables themselves and their relationship with the usability measures. Furthermore, the table also highlights the kind of experiments carried out. Controlled experiments are effective methods for understanding the immediate cause and effect between variables. However, a noticeable drawback of controlled experiments is the absence of external validity. The results might not be the same when applied in real-world settings. For instance, the simulation experiment on cars is a controlled environment, a driver has no control over the domain in real life. The usability experience of the driver might be different in natural settings and that might sometimes prove fatal.
Independent variables and their categorization
We identified seven techniques that researchers have used as shown in Fig. 5 . The quantitative experiments are the most used and the oldest technique used on voice assistants based on our data collected. The quantitative method is sometimes used as a standalone experiment and sometimes with other techniques [ 54 ]. It is worthy of notice that cars simulation experiments involving VA’s were first used in 2000. Other experiments on human communication with self-driving cars have been carried out since 1990’s. making it one of the oldest techniques for usability measurement. More accurate technique was introduced later, such as the interaction design. The interaction design employed by studies such as [ 61 ] provides a real-time experiment scenario. This avoids the drawback such as bias when using quantitative methods. Factorial design studies are majorly used by studies that compare two or more entities in a case study [ 55 ]. They are utilized mainly by studies using two or more independent variables together.
Technique used in our studies over the span period of time
Usability Measure (Dependent Variable)
This subsection of our study focuses on the usability measurement of our research. Moreover, the findings are used to answer RQ 1 and RQ 3 . The ISO 9241-11 framework grouped usability measures into three categories; effectiveness, efficiency, and satisfaction. According to the ISO 9241-11 framework, “effectiveness is the accuracy and completeness with which users achieve specified goals.”, Whereas “Efficiency is the resources expended concerning accuracy and completeness in which users achieve goals” and “satisfaction is the freedom from discomfort and positive attitudes towards the use of the product” [ 18 ].
In numerous studies, the usability measures used were clearly outside the scope of the ISO 9241-11 framework. In total, we identified three additional usability categories attitude, machine voice (anthropomorphism), and cognitive load. The graphical representation of the different usability measures identified in this study is presented in Figs. 6 and and7. 7 . Futhermore, the figures also highlights the percentage of studies that used the mentioned usability measures in the ISO 9241-11 framework and those that are outside the framework. Based on our compiled result, the user satisfaction and effectiveness are the earliest usability measures used when measuring VA’s usability. Some studies used performance and productivity as subthemes to measure effectiveness [ 62 ]. The measure of usability has been carried out both subjectively and objectively. For instance, studies have measured the VA effectiveness by subjective means by using quantitative methods such as questionnaire tools [ 72 ]. In contrast, other studies have used objective methods such as average completed interaction [ 69 ]. Multiple usability measures are sometimes applied in the same research; for instance some studies measured effectiveness alongside efficiency and satisfaction [ 66 , 70 ]. Learnability, optimization, and ease of use have been used as subthemes to measure efficiency. Interactive design is the most effective experiment that provides real-time results employed [ 56 , 79 ]. The ISO 9241-11 framework works well with effectiveness, efficiency, and satisfaction; however, the users have more expectations from the voice assistant with the recent advancement of VA capabilities. Our compiled result showed that more than half of the studies are not carried out in accordance with the standard ISO 9241-11 framework (Fig. 7 ). The other usability measures we identified outside the ISO 9241-11 framework are attitude, machine voice, and cognitive load.
Usability measurement used over the years on our compiled articles
Percentage of ISO 9241–11 framework usability measures and non ISO 9241–11
Attitude is a set of emotions, beliefs, and behavior towards the voice assistants. Attitude results from a person’s experience and can influence user behavior. Attitude is subjected to change and is not constant. Understanding the user attitude towards the VA has become an active research area. Numerous studies have used different methods to measure subthemes of attitude such as trust, closeness, disclosure, smartness, and honesty [ 60 , 78 ]. Likeability is also a subtheme of attitude, and it has been used to measure the compatibility, trust, and strength between the user and VA’s [ 56 , 57 ]. Moreover, embodiment type affects the user attitude as well, A study highlighted how gaze affects the user attitude toward VA [ 59 ], and it shows VA with gaze creates trust.
We defined machine voice (anthropomorphism) as the user attribution of human characteristics and human similarity to the voice assistant. We considered machine voice an important usability measure that only applies to voice assistants due to their primary modality being the voice. Considering that fact, the measure of machine voice has also spiked currently it becomes obvious that it has been drawing a lot of interest. One of the direct purposes of the VA is to sound as humanly as possible. When the users will perceived the machines to be more human, it built more trust, which will result in a better usability experience.
The cognitive load might be mistaken for efficiency. Nevertheless, they are different. We defined cognitive load as the amount of mental capacity a person applies to communicate successfully with the VA. When it comes to VA, actions such as giving out commands require cognitive thinking and approach. The cognitive load is measured by specific characteristics unique to the VA, such as attention time during the use of the VA [ 76 ] and the user’s mental workload during use [ 77 ].
To answer RQ 1 ( can the ISO 9241–11 framework be used to measure the usability of the VA’s?), none of the existing works have used the ISO 9241-11 framework solely for the purpose of usability evaluation. It has been supplemented by other factors that we have presented above that are outside the scope of this framework.
Relationship Between the Independent variables and Usability Measures
After identifying the independent and dependent variables, in Tables Tables5 5 and and6 6 we show how they are inter-related for having a better understanding of the usability scenario of the VA’s. While Table Table5 5 focuses on the ISO 9241-11 specific factors, Table Table6 6 considers the non-ISO factors specifically.
Relationship between independent variables and ISO 9241–11 framework measurement
Relationship between independent variables and non- ISO 9241–11 framework measurement
The independent variables are grouped into categories and represented by table rows, with every category consisting of multiple independent variables. Moreover, the usability measures have been presented in the column of the table. Every usability measure is made up of different sub-themes, which are all presented on the table as well. The tables highlight the relationship between the independent and usability measures. An “X” mark present in each cell represents a study present between that independent variable and usability measure subtheme. Nonetheless, an empty cell indicates that there is no study carried out to link that relationship between the usability measure and independent variable.
Independent Variable and Usability Measures
Our study revealed what has been previously carried out in VA usability and revealed the gaps that are yet to be addressed. We analyzed the usability measures and their relationship to the so-called independent variables. There is an easy accessibility to VA’s due to the development of different embodiment types such as speakers, humanoids, and robots. However, there is so much less focus on embodiment types and their relationship to effectiveness and anthropomorphism, which needs more attention. Some relationship gaps and associations are apparent, while some are vague. For instance, the independent variable “ accent ”, has often been connected with its effectiveness on users. However, what is left unanswered is if the VA accents impart the same efficacy on users of the same or different genders. Another notable gap is gender and efficiency, with very few studies on that. This will be an essential aspect to understand and apply with the recent massive adoption of voice assistants in different contexts. Another obvious gap is the query expression relationship with any ISO 9241-11 framework measures. The query expression is how a user expresses their query to the voice assistants. The query expression has been known to increase the trust and attitude of the user towards the VA. However, its relationship to usability measures such as efficiency, satisfaction, and effectiveness is still under-researched. Knowing the right way to ask queries (questions) defines the type of response a user gets. An incorrect response will be received if the right question is expressed incorrectly. From a mental model, when a user has too much energy and thought to frame a question, it affects the VA efficiency and satisfaction. However, this has not been proven by any current study.
The VA response types increase effectiveness and trust. However, its relationship to user acceptance is still unknown. Another exciting intersection is the anthropomorphic cues and attitude, which results from anthropomorphic emotional response than a practical one. Attitude is an emotional response to a giving state, hence its strong connection with anthropomorphism. The attitude toward the VA is a highly researched area [ 86 ]. Trust, likeability, and acceptance are subthemes that focused on the attitude usability measure. This can be attributed to the importance of trust while using emergent technologies such as voice assistants. User trust in voice assistants is an essential aspect with the rise of IoT devices, and user mistrust affects the acceptance and effectiveness of the VA’s [ 87 ]. Multiple studies measured user trust while using machine voice categories as an independent variable. That could be attributed to the lack of GUI in VA. Furthermore, the voice modality must be enough to cultivate user trust. Noticeably subjective methods were widely employed when measuring the user attitudes; even though subjective measures often relate to the variables they are intended to capture; however, they are also affected by cognitive biases.
The ISO 9241-11 framework is an effective tool when measuring effectiveness, efficiency, and satisfaction. However, it is not applicable when measuring usability’s, such as attitude, machine voice, and mental load. These are all measurements that are uniquely associated with voice assistants. Therefore, the ISO 9241-11 framework could be expanded to include such usability aspects.
The factorial design adapts well when used in a matched subject design experiments [ 56 ]. Based on the studies collected, machine learning is not well used as an analytic tool in usability. This could be attributed to the technical aspects of machine learning and it is still relatively a new field. However, with machine learning third-party tools more analysis will be carried out. Wizard of Oz, and interactive design started gaining popularity in 2015–2021. Moreover, the Wizard of Oz and interactive techniques are more effective when using independent variables such as anthropomorphic cues. The anthropomorphic cue independent variables is used with Wizard of Oz. techniques and interaction design more than any other techniques. This could be recognized to the importance of using objective methods to avoid biased human responses. Furthermore, “machine voice” is a fairly popular usability measure. This could be attributed to the VA developers trying to give the VA a more human and intelligent attributes. The more users perceive the machine voice as intelligent and humanlike, the more they trust and adopt it. More objective technique methods should be created and used on the independent variables when measuring machine voice. Subjective techniques such as Quantitative methods are easy to use and straightforward. However, they can produce biased results.
Interactive design experiments are the most commonly used technique employed to measure the usability. However, the interaction depends on voice modality, making it different from the traditional interaction design that uses visual cues as part of its essential components. Moreover, interaction design also triggers an emotional response, which makes it effective when measuring user attitude. The absence of visual elements in interactive design used might debatably defeat the purpose of clear communication. A new standard of interaction design uniquely for voice modality should be done.
Future Works and Limitation
One limitation in our study was using a few databases as our articles source; in future studies, we intend to add more journal databases such as Scopus, and Taylor and Francis. The majority of the experiment studies we collected was conducted in a controlled environment; future studies will focus on usability measures and independent variables, that are used in natural settings; furthermore, the results can be compared together More studies should be carried out on objective techniques, also how they could cooperate with subjective techniques. This is vital because, with the rise of user expectations of voice assistants, it will be essential to understand how techniques complement each other in each usability measurement.
Our study aimed to understand what is currently employed for measuring voice assistant usability, and we identified the different independent variables, dependent variables, and the techniques used. Furthermore, we also focused on using the ISO 9241-11 framework to measure the usability of voices assistants. Our study classified five independent variable classes used for measuring the dependent variables. These separate classes were categorized based on the similarities between the member groups. Also, our study used the three usability measures in the ISO 9241-11 framework in conjunction with the other three to serve as the dependable variables. We uncovered that voice assistants such as car interface speakers were not studied enough, and currently, smart speakers have the most focus. Dependent variables such as machine voice (anthropomorphism) and attitude recently have more concentration than the old usability measures, such as effectiveness. We also uncovered that usability is dependent on the context of use, such as the same independent variables could be used in different usability measures. Our study highlights the relationship between the independent and dependent variables used by other studies. In conclusion, our study used the ISO 9241-11 to analyse usability. We also highlight what has been carried out on VA’s usability and what gaps are left. Moreover, we concluded even though there is a lot of usability measurement carried out, there are still many aspects that have not been researched. Furthermore, the current ISO 9241-11 framework is not suitable for measuring the recent advancement of VA because the user needs and expectation have changed with the rise of technology. Using the ISO 9241-11 framework will create ambiguity in explaining some usability measures such as machine voice, attitude and cognitive load. However, it has the potential to be a foundation for future VA usability frameworks.
This study was funded by The Asahi Glass Foundation.
The author declares that they have no conflict of interest.
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Faruk Lawal Ibrahim Dutsinma, Email: [email protected] .
Suree Funilkul, Email: ht.ca.ttumk.tis@eerus .
Jonathan H. Chan, Email: ht.ca.ttumk.tis@nahtanoj .
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IRJET- A Literature Review on Smart Assistant
Smart assistants are a boon for everyone in this new era of 21 st century. Where we can ask questions to machines and interact with smart assistants. This Technology attracts almost everyone in the world in many ways like smart phones, laptops, computers, etc. It is a Smart Assistant with Voice Recognition Intelligence, which takes the user input in the form of voice or in the form of text and processes it after processing it will return the output in various forms like search result is dictated to the end user. Some of the smart assistants are like Google Assistant, SIRI and Alexa. They cannot do Voice recognition, and human interaction are the issues which are not solved yet. The issues with Google assistant, SIRI that they need WIFI and internet connection for user interaction. Google Assistant" which is used in Android Phones. But this Application always works with Internet Connections. But our Proposed System has the capability to work with without Internet Connectivity as well.
There has been a lot of advancement in the field of Artificial Intelligence. Every person uses mobile phones or laptop in his daily life which have personal assistants. The proposed system uses artificial intelligence algorithms for the assistant to work. The bot does all the work of the commonly used chatbot assistants but also deploys new functionalities. It also considers user's emotion while talking. For an example, the chatbot tries to cheer up the user whenever he is upset or feeling sad. The system also provides the user with the facility to teach the bot himself. This allows user to adjust the bot according to himself and also correct the bot when it's wrong. The technologies being used in the system are Machine-Learning (ML), Chatbot, Image processing and Neural Network. The proposed system can de deployed on personal computers, laptops, it can also be used in robotics and simulations.
Today's World is moving to digitalization where everything is made easy and comfortable for people. A smart home can be easily designed with the help of automated machines and wireless connectivity. Most of the existing systems which are available in the market use a Raspberry Pi or Arduino chipset. These are programmed to control a set of devices inside a house, which are given instructions using a mobile application or a web-based UI. It is proposed to have a system that focuses on controlling the device using voice recognition and artificial intelligence while being interactive as well. This is accomplished by making use of the open-sourced API of Google Assistant by Google Inc. Smart automated home application system using IoT (Internet of Things) have designed through which basic house facility can be handled by the device from any place such as ON and OFF of Light, Fan, AC. All the devices can be easily handled with the help of device NodeMCU ESP8266, Internet Connection. Different sensors are connected to node MCU and can operate from any part of the world with help of Adafruit. This makes the life of the common man very easy.
Virtual assistant is boon for everybody during this new era of 21st century. It has paved way for a replacement technology where we will ask inquiries to machine and may interact with IV As people do with humans. This new technology attracted almost whole world in some ways like smart phones, laptops, computers etc. a number of the many VPs are like Siri, Google Assistant, Cortana, and Alexa. Voice recognition, contextual understanding and human interaction are the problems which aren't solved yet during this IVAs. So, to unravel those issues 100 users participated a survey for this research and shared their experiences. All users' task was to ask questions from the survey to all or any personal assistants and from their experiences this research paper came up with the particular results. Consistent with that results many services were covered by these assistants but still there are some improvements required in voice recognition, contextual understanding and hand free interaction. After addressing these improvements in IVAs will certainly increased its use is that the main goal for this research paper This application is along these lines created in order that it can oversee content need to by user, analyze the voice properties and choose the direction in voice. We also present a completely unique approach that uses pitch feature of voice within the interest of identifying the speaker's gender with as little speech as possible. We also investigate the cross comparison of three different algorithm such GMM, HMM, SVM of a model trained on English speakers. And finding the simplest suitable algorithm for this kind of approach work.
In today's world of Artificial Intelligence, virtual assistants are becoming more and more popular. Many virtual assistants are available in the market like Amazon's Alexa, Microsoft's Cortana. Anyone can access these virtual assistants by using their wake-up word. So, security is the main issue with these virtual assistants. In this paper, we proposed a virtual assistant ALLY for laptops or computers. It has security features like face recognition, audio matching, and OTP verification via email. If the user successfully completes any of the security levels, then that user can give commands to ALLY. That means, only an authorized person has access to ALLY. Using these security features, we can prevent unauthorized access to the virtual assistant. ALLY can perform various functionalities like sending email, taking notes, telling today's news, telling weather conditions, managing calendars, and much more. We have added advanced features like data analysis and then visualize the results. ALLY uses the power of Python libraries like gTTS, speech recognition, TensorFlow, and pygame resulting in a powerful and intelligent virtual assistant.
In the past few years, Artificial Intelligence (AI) has grown so much in the field of science and technology. Voice assistant incorporate AI by using cloud computing and Natural Language Processing (NLP). In AI, NLP is used to communicate with the user in natural language. There are lots of devices which use AI nowadays such as AI Voice assistant. There are millions of households who have been using voice assistants for their personal use. Most common devices which uses voice assistant are smart speakers. The main idea of this paper is to make a personal assistant to provide security to especially abled and elderly people.
In this paper we introduce, BRAIN-THE A.I. a personal voice assistant that use to take the user commands as input and perform tasks based on the user commands. It provides more efficient and natural interaction with support of multiple voice commands in the same utterance. This assistant has a unique face recognition technique through which only the authorized user can provide the command to the assistant and can perform their various tasks on system. Our proposed system reaches out to help our society by making their work easier as this system can tell the news, search what you want, send email by only your voice command, play game with you, set reminders, tell the location, forecast weather, can tell horoscope of you and endless number of tasks can be done by this. Thus our system can be used for the doing the multipurpose tasks in robust and flexible approaches.
Everything in the twenty-first century is automated, including items we use every day like bus doors, air conditioning systems, and turning everything on with a single click, among other things. The current study provides a newer notion of voice-controlled gadget that detects one's speech, processes the request, and details of other associated information in this fast-paced environment. We need to develop gadgets with built-in speech recognition that can recognize a person's speech even in a crowded environment, as well as a facial recognition system. We thought making a personal assistant in Python would be fun. The device will take sounds through the device's microphone, process the human's query, and respond to the human with the necessary results. If you ask the gadget to play a video on your computer, for example, it will open YouTube and play the video you choose. The Python Speech Recognition module can be used to do speech recognition. Because of its high quality, we use the Google Speech API.
A voice assistant is a software that interprets human voice and responds via speech synthesis to come up with a utility through a specific application. Some of the most famous voice assistants are Amazon's Alexa, Apple's Siri, Google's Assistant and Microsoft's Cortana, they are implanted in smart devices. Users can get the answers to their queries by asking their questions to the assistant. Voice assistant also help us to control home automation devices, and manage other basic tasks such as call, message, music apps and many more things. Using this assistant, users would be able to control our YouTube, could solve their arithmetic questions, and also could be able to search any information on the internet. Voice assistants ease our daily life as it does different functions fastly and also reduces time and make searching more smoother. It can also help visually impaired, physically challenged people and illiterate people as they can speak up their questions directly instead of typing.
Speech conversion by a leading industry-GOOGLE. Using the following libraries mention ahead, AVAYA is programmed in such a way to provide better human machine interaction with some personnel security attributes added such as Face-Recognition and Voice-Recognition.
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30 compelling virtual assistant articles you’ll want to read
Virtual assistants provide cost-effective support services so you can focus on your business’ core functions. Whether you manage a large enterprise or a small business, VAs can help take your company to new heights.
However, finding the right virtual assistant and managing them properly can seem daunting.
Thankfully, there are loads of informative virtual assistant resources available online.
To make it easier for you, we’ve created a list of the most useful virtual assistant articles on the internet.
If you want to know what a virtual assistant does, how to manage them, which industries they suit, or where to find the best ones, you’ll discover all you need to know in these articles.
This article includes:
(Jump to a specific section using the below links)
- 25 Informative Virtual Assistant Articles
- General Virtual Assistant Information
- Managing Virtual Assistants
- Industry-Specific Virtual Assistants
- Virtual Assistants in Specific Countries
- 5 Bonus Virtual Assistant Articles
Let’s get started.
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25 informative virtual assistant articles
Below is a list of articles to guide you through the entire process of hiring and managing a virtual assistant (VA).
1. General virtual assistant information
Whether you’re a small business owner, fledgling entrepreneur, or running a large corporation, these articles will help you understand the fundamentals of hiring a virtual assistant.
A. Virtual assistants: What they do & how to hire
Discover what exactly a virtual assistant is, what they do, how to hire one, and how much they will cost working full-time or part-time.
B. 5 key reasons to hire a virtual assistant for your business
If you’re wondering how a virtual assistant can benefit you, discover the five key reasons for hiring a virtual assistant every business owner should know.
C. 100 tasks you can outsource to virtual assistant services
Interested in outsourcing your mundane tasks ?
Find out what task you can outsource to a virtual assistant.
Examples include making travel arrangements, social media management, customer support, project management, and digital marketing tasks.
D. Virtual assistant vs. employee: Which is right for you?
Discover whether you should hire a virtual assistant (a remote independent contractor/ freelancer) or an in-house employee. Make the right choice after exploring the advantages and disadvantages of both types of team members.
E. Top 25 virtual assistant websites for VA services
There are countless websites where you can find individuals and companies offering virtual assistant services, so how do you choose the right one? Find out the key features to look for in a VA website and the 25 best virtual assistant websites today.
F. How much does it cost you to hire a virtual assistant?
Need help finding a virtual assistant with the right skill set that fits your budget?
Explore the factors that determine a VAs salary and how much to pay your virtual assistant.
G. How to start a virtual assistant business
If you’re interested in being self-employed and starting your own virtual assistant business, it’s now easier than ever. But you’ll need more than just an internet connection.
Discover what it takes to start a successful VA business, as well as the pros and cons of doing so.
2. Managing virtual assistants
Once you know the virtual assistant basics, you’ll need to learn how to manage them effectively. Here are a few informative articles to help.
A. 51 best virtual sssistant software tools to optimize productivity
This list of 51 of the top tools will help you decide on the best software for optimization of your virtual assistants’ productivity.
B. 10 smart tips for successful remote employee productivity management
Since most virtual assistants work remotely, managing their productivity may be tricky. Here are 10 tips to help you monitor your virtual assistants’ performance and ensure they’re working to their full potential.
C. The guide to virtual assistant training (benefits, courses, FAQs)
Once you’ve hired the best virtual assistant, you’ll need to train them. Discover what to look for in a training program, three of the best virtual assistant courses, and the training cost for each.
D. Virtual assistant contracts: The ultimate guide (process + tips)
Virtual assistant contracts aren’t the same as employee contracts.
Since your VA will be working from a remote location, it’s important to specify the ground rules in their contract, including job description, working hours, and so on.
Find out the three main forms of contracts and what to include in your virtual employee contract.
E. Top 10 virtual team communication tools (features, pricing)
Once you hire your virtual assistant, you’ll need an efficient means of communication.
We’ve reviewed the top 10 communication tools to help you easily choose the best one for your company.
3. Industry-specific virtual assistants
If you’re looking for more industry-specific information, the following articles will help you hire and manage the right virtual assistants for your industry.
A. How to hire and manage a healthcare virtual assistant (tips + tools)
Virtual assistants have become an indispensable part of the healthcare industry, handling tasks like updating medical records, billing patients, scheduling appointments, etc.
Discover how to hire a dedicated virtual assistant for your healthcare business, plus get tips and tools to manage them effectively.
B. Virtual assistant business operations: How to hire & manage
Instead of hiring an administrative assistant that works within your office space, you can hire a virtual office assistant or an executive assistant who works remotely from their home office.
This person can handle time-consuming tasks, like fielding incoming calls, so you can avoid wasting time on unproductive phone calls, and focus on qualified client leads and potential customers.
C. Ultimate guide to virtual assistant call center services (tips & tools)
Automating your call answering or adopting call center AI (artificial intelligence) may seem tempting, but most people prefer hearing natural language rather than talking to machines. A potential client will appreciate speaking to a real person rather than a Siri like voice.
So instead of adopting AI virtual assistance, opt for human VA call center services.
Read our guide for more on the benefits, hiring, and management of call center VAs.
D. What you need to know about virtual assistant bookkeeping
If you’re a business owner or manager who would rather avoid the expense of hiring a full-time employee, a virtual bookkeeping assistant is a good idea. They can assist you with managing your accounts, calculating taxes, etc.
Here’s everything you need to know about bookkeeping VAs.
E. Ultimate guide to social media virtual assistants (tools + tips)
A good social media virtual assistant can help you save time by managing LinkedIn, Facebook, or any other social media account for your business.
Discover tips and tools to recruit and manage a social media virtual assistant successfully.
F. How to hire and manage a legal virtual assistant (ultimate guide)
Businesses in the legal field have to deal with an enormous amount of administrative tasks, like legal data entry, transcription, and legal research. Legal virtual assistants can ease the heavy workload on the entire team.
G. How to hire a real estate virtual assistant
Learn how hiring a real estate virtual assistant can help you close more deals. Also, discover the different tasks VAs can take on in the real estate industry, like data entry, scheduling meetings with prospective clients, and so on.
H. How to successfully hire and manage digital marketing virtual assistants
Digital marketing involves using the internet, mobile devices, social media, search engines, display advertising, and other online channels to reach consumers.
However, it requires a lot of time and effort – a problem a virtual assistant can help solve.
Discover how to hire virtual professionals on a once-off basis for a specific task like adding opt-ins during web design. Or recruit VAs for more regular tasks like email marketing and search engine optimization (SEO).
4. Virtual assistants in specific countries
If you run a small business or are looking to minimize expenses, sourcing virtual staff internationally is a great solution.
The following articles can help you make informed decisions regarding where you source your virtual assistants from:
A. 10 best virtual assistant countries for finding excellent VAs
The popularity of virtual assistants has skyrocketed recently. But which country has the best VAs? Find out the top ten VA countries and what they have to offer.
B. Virtual assistant China: Top services, tips
Low labor costs and a wide variety of services on offer have made China, a top provider of virtual assistant services. Discover the best platforms and tips for hiring a VA in China.
C. Virtual assistant Philippines: How to hire, pay & more
The Philippines has emerged as a leading provider of virtual assistants due to its well-educated workforce and high level of English proficiency. Explore how to hire an affordable, professional, and dedicated virtual assistant suited to your industry.
D. The top 5 virtual assistant companies in the USA
Whether you’re looking for an ecommerce site developer or an office assistant, there are dozens of USA-based virtual assistant service providers to choose from.
Fortunately, you don’t have to research them all; we’ve compiled a list of the top five, including Upwork and Belay.
E. Virtual assistant Australia: Top services, pricing, & more
Find the best Australian virtual assistant company to suit your needs and how much it’ll cost you. Or, if you’re interested in a virtual assistant job, discover how to become a VA in Australia.
Next, let’s check out a few additional virtual assistant blog posts that you may find useful.
5 bonus virtual assistant articles
We’ve combed through the internet to find some practical advice on virtual assistants from other trusted sources.
A. 6 tips for hiring international virtual assistants
Get tips on how you can save money by hiring international VAs for basic admin task management like scheduling appointments with multiple clients, content writing, answering emails, etc.
B. 8 reasons why hiring a healthcare virtual assistant can benefit your practice
If you run a medical practice, a healthcare virtual assistant can help your business run smoothly without costing you an arm and a leg.
C. Level up your content with a video editing virtual assistant
Learn how to leverage great content created by a video editing virtual assistant to expand your brand’s reach and grow your company.
D. 20 qualities of a good virtual assistant
Discover five important qualities to look for when hiring a virtual assistant for your business.
E. The 7 best apps to hire a real personal assistant through your phone
Convenience is one of the main reasons entrepreneurs and managers seek virtual assistance. One of the most convenient ways of sourcing virtual professionals is via your mobile phone.
Here are seven of the best apps you can use to find a virtual personal assistant.
If you’re looking to free up your time to focus on key business activities and expand your business, hiring a virtual assistant is the way to go.
But, to find the right VA for your business, you’ll need to do your research first.
This comprehensive list of articles should help you get started. And for the latest information and developments on the virtual assistant industry, feel free to visit the Time Doctor blog .
7 practical strategies for employee retention
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International Symposium on Signal Processing and Intelligent Recognition Systems
SIRS 2018: Advances in Signal Processing and Intelligent Recognition Systems pp 190–201 Cite as
Survey on Virtual Assistant: Google Assistant, Siri, Cortana, Alexa
- Amrita S. Tulshan 15 &
- Sudhir Namdeorao Dhage 15
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Part of the Communications in Computer and Information Science book series (CCIS,volume 968)
Virtual assistant is boon for everyone in this new era of 21st century. It has paved way for a new technology where we can ask questions to machine and can interact with IVAs as people do with humans. This new technology attracted almost whole world in many ways like smart phones, laptops, computers etc. Some of the significant VPs are like Siri, Google Assistant, Cortana, and Alexa. Voice recognition, contextual understanding and human interaction are the issues which are not solved yet in this IVAs. So, to solve those issues 100 users participated a survey for this research and shared their experiences. All users’ task was to ask questions from the survey to all personal assistants and from their experiences this research paper came up with the actual results. According to that results many services were covered by these assistants but still there are some improvements required in voice recognition, contextual understanding and hand free interaction. After addressing these improvements in IVAs will definitely increased its use is the main goal for this research paper.
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Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada
Prof. Sri Krishnan
Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan
Prof. Kuan-Ching Li
University of Naples Federico II, Naples, Italy
Electrical Engineering Department, Indian Institute of Technology Patna, Patna, India
Dr. Maheshkumar H. Kolekar
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Tulshan, A.S., Dhage, S.N. (2019). Survey on Virtual Assistant: Google Assistant, Siri, Cortana, Alexa. In: Thampi, S., Marques, O., Krishnan, S., Li, KC., Ciuonzo, D., Kolekar, M. (eds) Advances in Signal Processing and Intelligent Recognition Systems. SIRS 2018. Communications in Computer and Information Science, vol 968. Springer, Singapore. https://doi.org/10.1007/978-981-13-5758-9_17
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Jewish Studies Program To Debut In Spring 2024 Alongside Exciting Offerings
The College of Arts and Sciences invites the campus and community to a Nov. 6 kickoff event celebrating a noteworthy first — the creation of a new Jewish Studies program at Texas A&M University, to be housed within the Department of Global Languages and Cultures .
No tickets or registration is required for the free public event, which will feature an afternoon symposium and evening keynote lecture marking the culmination of a multi-year effort by professors, staff and donors to launch the program’s first course offerings in the spring 2024 semester.
The Jewish Studies program is due in large part to Donald Zale ’55 and Gerald Ray ’54, both Texas A&M former students and members of the Corps of Cadets. They have remained friends ever since. Zale and Ray envision great potential for Texas A&M to host a Jewish Studies program as one of the largest universities in the United States.
“Texas A&M University has one of the best populations of friendly students who lead by example,” Zale said. “It’s a perfect place for Jewish students and for the families of Jewish students. It’s gratifying for me to see this program start. Hopefully, it will attract more Jewish students to the university.
“I bleed maroon and white. I’ve been an Aggie since 1951. I’m 90 years old, and I’ve traveled all over the country and many parts of the world. It is just different at Texas A&M. There is a spirit here and a unique definition. It’s a welcoming environment, and I think we need to expand the opportunities.”
Ray and Zale entrusted Dr. Ashley Passmore , an instructional assistant professor in Global Languages and Cultures who serves as the program’s coordinator, to advocate for the establishment of the Jewish Studies program — a process that took six years of groundwork and research.
“As an educator, I’m excited to have the resources of a formal Jewish Studies program to elevate people who are working in this field and get them the visibility they otherwise wouldn’t have,” Passmore said. “This is not necessarily just for Jewish students. In fact, it’s for people of all backgrounds. On Nov. 6, we wish to engage students and faculty in conversation on contemporary research at Texas A&M in the field of Jewish Studies. We invite students to consider taking new classes being offered in Jewish Studies or to become a Jewish Studies minor.”
Passmore noted that the symposium will showcase the depth and breadth of the Jewish Studies research already underway at Texas A&M, with an emphasis on its global scope and multidisciplinary nature. Scholars will present as part of two sessions from 1:30 p.m. to 5 p.m. Each session will be followed by a question-and-answer opportunity. The evening will conclude with a keynote lecture by Dr. Victoria Aarons at 5:45 p.m. Aarons, who holds the O.R. and Eva Mitchell Distinguished Professor of Literature at Trinity University, is an esteemed scholar in the field of American Jewish and Holocaust Studies. She has written more than 90 scholarly articles and authored or edited 12 books.
Nov. 6 Symposium Schedule At A Glance
1:30 p.m.-3 p.m. “Ethical Lessons of Holocaust Research” Melbern G. Glasscock Center for Humanities Research Glasscock Library (GLAS 311) Featuring Drs. Joe Golsan , Adam Seipp and David Brenner
3:30 p.m.-5 p.m. Melbern G. Glasscock Center for the Humanities Research Glasscock Library (GLAS 311) “Crossroads of Hispanic and Jewish Studies” Featuring Dr. Esther Quintana , Gabrielle Lyle and Jillian Glantz
5:45 p.m.-6:45 p.m. “Generations of Memory in Holocaust Graphic Novels” Harrington Education Center Classroom Building (HECC 108)
The Jewish Studies minor will offer courses and programs for students to “study Jews and Judaism within the broader context of dominant societies and the spectrum of the arts, humanities and social sciences.” One new course offering for the spring 2024 semester will be Introduction to Jewish Studies (JWST 201), taught by Brenner.
“For me, this program is the fulfillment of a dream,” Brenner said. “Not only am I an educator who is originally from this part of Texas, but I am also a scholar who has been working at the intersections of humanities and Jewish Studies for nearly three decades now. The study of the Jewish people throughout history offers us useful tools for understanding other members of societies in which Jews have lived. In this inaugural course of the new Jewish Studies minor, students will explore Jewish history, culture and identity throughout the millennia and in the modern world. Like the Jewish Studies minor itself, the course is open to students from any major.”
Another course offering for spring 2024 will be Representations of the Holocaust (GERM 441), taught by Passmore and exploring innovative representations of Holocaust experiences and memories in multimedia forms, ranging from pop-up monuments to virtual spaces like gaming platforms. Both courses will give students priority consideration for a study abroad trip to Vienna and Budapest during spring break 2024. Students will visit significant Jewish heritage sites, museums and synagogues, and engage in academic discussions to foster a holistic appreciation of the Jewish experience in Vienna and Budapest to deepen their understanding of Jewish history, traditions and contributions.
This is only the beginning, according to Passmore. Future courses in the Jewish Studies program will focus on cinema, philosophy, archaeology, communication, Hebrew and much more. In addition, the Jewish Studies minor may be paired with a variety of majors for students who wish to pursue professional careers in law, medicine, journalism, business or other areas. Additional plans for the program include ongoing seminars, research clusters, expanded experiences abroad for students, working groups and guest lectures from visiting scholars.
“The vision of the program is to create a space for diverse interests across disciplines that are connected to the wider idea of Jewish Studies to come together,” Passmore said. “I’m really excited about the possibility of our Jewish Studies program having connections with other research institutes around the world. Naming something as a research and knowledge entity creates a new foundation for growth. We’re such an internationally connected university that it makes sense that an incredibly international population, history and culture should also be part of our knowledge and identity.”
Media contact: Shana K. Hutchins, [email protected]
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